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Description of Statistical Computation

Author's title

Author*The author of this computation has been verified*
R Software Modulerwasp_multipleregression.wasp
Title produced by softwareMultiple Regression
Date of computationSun, 07 Dec 2014 11:27:23 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2014/Dec/07/t1417951684tkqz4mx4o8nriu4.htm/, Retrieved Thu, 16 May 2024 10:48:30 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=263726, Retrieved Thu, 16 May 2024 10:48:30 +0000
QR Codes:

Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact120

Tree of Dependent Computations

Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Multiple Regression] [Motivatie_Zelfver...] [2014-12-07 11:27:23] [4ce2356216df8db4950cd852fec912aa] [Current]
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Dataset

Dataseries X:
Download CSV
Histogram
Boxplots 
12 26 50 4 12.9
8 57 62 4 12.2
11 37 54 5 12.8
13 67 71 4 7.4
11 43 54 4 6.7
10 52 65 9 12.6
7 52 73 8 14.8
10 43 52 11 13.3
15 84 84 4 11.1
12 67 42 4 8.2
12 49 66 6 11.4
10 70 65 4 6.4
10 52 78 8 10.6
14 58 73 4 12.0
6 68 75 4 6.3
12 62 72 11 11.3
14 43 66 4 11.9
11 56 70 4 9.3
8 56 61 6 9.6
12 74 81 6 10.0
15 65 71 4 6.4
13 63 69 8 13.8
11 58 71 5 10.8
12 57 72 4 13.8
7 63 68 9 11.7
11 53 70 4 10.9
7 57 68 7 16.1
12 51 61 10 13.4
12 64 67 4 9.9
13 53 76 4 11.5
9 29 70 7 8.3
11 54 60 12 11.7
12 58 72 7 9.0
15 43 69 5 9.7
12 51 71 8 10.8
6 53 62 5 10.3
5 54 70 4 10.4
13 56 64 9 12.7
11 61 58 7 9.3
6 47 76 4 11.8
12 39 52 4 5.9
10 48 59 4 11.4
6 50 68 4 13.0
12 35 76 4 10.8
11 30 65 7 12.3
6 68 67 4 11.3
12 49 59 7 11.8
12 61 69 4 7.9
8 67 76 4 12.7
10 47 63 4 12.3
11 56 75 4 11.6
7 50 63 8 6.7
12 43 60 4 10.9
13 67 73 4 12.1
14 62 63 4 13.3
12 57 70 4 10.1
6 41 75 7 5.7
14 54 66 12 14.3
10 45 63 4 8.0
12 48 63 4 13.3
11 61 64 4 9.3
10 56 70 5 12.5
7 41 75 15 7.6
12 43 61 5 15.9
7 53 60 10 9.2
12 44 62 9 9.1
12 66 73 8 11.1
10 58 61 4 13.0
10 46 66 5 14.5
12 37 64 4 12.2
12 51 59 9 12.3
12 51 64 4 11.4
8 56 60 10 8.8
10 66 56 4 14.6
5 37 78 4 12.6
10 59 53 6 NA
10 42 67 7 13.0
12 38 59 5 12.6
11 66 66 4 13.2
9 34 68 4 9.9
12 53 71 4 7.7
11 49 66 4 10.5
10 55 73 4 13.4
12 49 72 4 10.9
10 59 71 6 4.3
9 40 59 10 10.3
11 58 64 7 11.8
12 60 66 4 11.2
7 63 78 4 11.4
11 56 68 7 8.6
12 54 73 4 13.2
6 52 62 8 12.6
9 34 65 11 5.6
15 69 68 6 9.9
10 32 65 14 8.8
11 48 60 5 7.7
12 67 71 4 9.0
12 58 65 8 7.3
12 57 68 9 11.4
11 42 64 4 13.6
9 64 74 4 7.9
11 58 69 5 10.7
12 66 76 4 10.3
12 26 68 5 8.3
14 61 72 4 9.6
8 52 67 4 14.2
10 51 63 7 8.5
9 55 59 10 13.5
10 50 73 4 4.9
9 60 66 5 6.4
10 56 62 4 9.6
12 63 69 4 11.6
11 61 66 4 11.1
9 52 51 6 4.35
11 16 56 4 12.7
12 46 67 8 18.1
12 56 69 5 17.85
7 52 57 4 16.6
12 55 56 17 12.6
12 50 55 4 17.1
12 59 63 4 19.1
10 60 67 8 16.1
15 52 65 4 13.35
10 44 47 7 18.4
15 67 76 4 14.7
10 52 64 4 10.6
15 55 68 5 12.6
9 37 64 7 16.2
15 54 65 4 13.6
12 72 71 4 18.9
13 51 63 7 14.1
12 48 60 11 14.5
12 60 68 7 16.15
8 50 72 4 14.75
9 63 70 4 14.8
15 33 61 4 12.45
12 67 61 4 12.65
12 46 62 4 17.35
15 54 71 4 8.6
11 59 71 6 18.4
12 61 51 8 16.1
6 33 56 23 11.6
14 47 70 4 17.75
12 69 73 8 15.25
12 52 76 6 17.65
12 55 68 4 16.35
11 41 48 7 17.65
12 73 52 4 13.6
12 52 60 4 14.35
12 50 59 4 14.75
12 51 57 10 18.25
8 60 79 6 9.9
8 56 60 5 16
12 56 60 5 18.25
12 29 59 4 16.85
11 66 62 4 14.6
10 66 59 5 13.85
11 73 61 5 18.95
12 55 71 5 15.6
13 64 57 5 14.85
12 40 66 4 11.75
12 46 63 6 18.45
10 58 69 4 15.9
10 43 58 4 17.1
11 61 59 4 16.1
8 51 48 9 19.9
12 50 66 18 10.95
9 52 73 6 18.45
12 54 67 5 15.1
9 66 61 4 15
11 61 68 11 11.35
15 80 75 4 15.95
8 51 62 10 18.1
8 56 69 6 14.6
11 56 58 8 15.4
11 56 60 8 15.4
11 53 74 6 17.6
13 47 55 8 13.35
7 25 62 4 19.1
12 47 63 4 15.35
8 46 69 9 7.6
8 50 58 9 13.4
4 39 58 5 13.9
11 51 68 4 19.1
10 58 72 4 15.25
7 35 62 15 12.9
12 58 62 10 16.1
11 60 65 9 17.35
9 62 69 7 13.15
10 63 66 9 12.15
8 53 72 6 12.6
8 46 62 4 10.35
11 67 75 7 15.4
12 59 58 4 9.6
10 64 66 7 18.2
10 38 55 4 13.6
12 50 47 15 14.85
8 48 72 4 14.75
11 48 62 9 14.1
8 47 64 4 14.9
10 66 64 4 16.25
14 47 19 28 19.25
9 63 50 4 13.6
9 58 68 4 13.6
10 44 70 4 15.65
13 51 79 5 12.75
12 43 69 4 14.6
13 55 71 4 9.85
8 38 48 12 12.65
3 45 73 4 19.2
8 50 74 6 16.6
12 54 66 6 11.2
11 57 71 5 15.25
9 60 74 4 11.9
12 55 78 4 13.2
12 56 75 4 16.35
12 49 53 10 12.4
10 37 60 7 15.85
13 59 70 4 18.15
9 46 69 7 11.15
12 51 65 4 15.65
11 58 78 4 17.75
14 64 78 12 7.65
11 53 59 5 12.35
9 48 72 8 15.6
12 51 70 6 19.3
8 47 63 17 15.2
15 59 63 4 17.1
12 62 71 5 15.6
14 62 74 4 18.4
12 51 67 5 19.05
9 64 66 5 18.55
9 52 62 6 19.1
13 67 80 4 13.1
13 50 73 4 12.85
15 54 67 4 9.5
11 58 61 6 4.5
7 56 73 8 11.85
10 63 74 10 13.6
11 31 32 4 11.7
14 65 69 5 12.4
14 71 69 4 13.35
13 50 84 4 11.4
12 57 64 4 14.9
8 47 58 16 19.9
13 47 59 7 11.2
9 57 78 4 14.6
12 43 57 4 17.6
13 41 60 14 14.05
11 63 68 5 16.1
11 63 68 5 13.35
13 56 73 5 11.85
12 51 69 5 11.95
12 50 67 7 14.75
10 22 60 19 15.15
9 41 65 16 13.2
10 59 66 4 16.85
13 56 74 4 7.85
13 66 81 7 7.7
9 53 72 9 12.6
11 42 55 5 7.85
12 52 49 14 10.95
8 54 74 4 12.35
12 44 53 16 9.95
12 62 64 10 14.9
12 53 65 5 16.65
9 50 57 6 13.4
12 36 51 4 13.95
12 76 80 4 15.7
11 66 67 4 16.85
12 62 70 5 10.95
6 59 74 4 15.35
7 47 75 4 12.2
10 55 70 5 15.1
12 58 69 4 17.75
10 60 65 4 15.2
12 44 55 5 14.6
9 57 71 8 16.65
3 45 65 15 8.1

Tables (Output of Computation)





Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 9 seconds \tabularnewline
R Server & 'Sir Ronald Aylmer Fisher' @ fisher.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263726&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]9 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Sir Ronald Aylmer Fisher' @ fisher.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263726&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263726&T=0

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time9 seconds
R Server'Sir Ronald Aylmer Fisher' @ fisher.wessa.net






Multiple Linear Regression - Estimated Regression Equation
CONFSOFTTOT[t] = + 10.8218 + 0.0460526AMS.I[t] -0.0322419AMS.E[t] -0.0812149AMS.A[t] + 0.00721696TOT[t] + e[t]

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Estimated Regression Equation \tabularnewline
CONFSOFTTOT[t] =  +  10.8218 +  0.0460526AMS.I[t] -0.0322419AMS.E[t] -0.0812149AMS.A[t] +  0.00721696TOT[t]  + e[t] \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263726&T=1

[TABLE]
[ROW][C]Multiple Linear Regression - Estimated Regression Equation[/C][/ROW]
[ROW][C]CONFSOFTTOT[t] =  +  10.8218 +  0.0460526AMS.I[t] -0.0322419AMS.E[t] -0.0812149AMS.A[t] +  0.00721696TOT[t]  + e[t][/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263726&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263726&T=1

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Estimated Regression Equation
CONFSOFTTOT[t] = + 10.8218 + 0.0460526AMS.I[t] -0.0322419AMS.E[t] -0.0812149AMS.A[t] + 0.00721696TOT[t] + e[t]






Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)10.82181.47597.3322.57596e-121.28798e-12
AMS.I0.04605260.01406013.2750.001191410.000595705
AMS.E-0.03224190.0184581-1.7470.08180320.0409016
AMS.A-0.08121490.0413841-1.9620.05072390.0253619
TOT0.007216960.03994010.18070.8567410.428371

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Ordinary Least Squares \tabularnewline
Variable & Parameter & S.D. & T-STATH0: parameter = 0 & 2-tail p-value & 1-tail p-value \tabularnewline
(Intercept) & 10.8218 & 1.4759 & 7.332 & 2.57596e-12 & 1.28798e-12 \tabularnewline
AMS.I & 0.0460526 & 0.0140601 & 3.275 & 0.00119141 & 0.000595705 \tabularnewline
AMS.E & -0.0322419 & 0.0184581 & -1.747 & 0.0818032 & 0.0409016 \tabularnewline
AMS.A & -0.0812149 & 0.0413841 & -1.962 & 0.0507239 & 0.0253619 \tabularnewline
TOT & 0.00721696 & 0.0399401 & 0.1807 & 0.856741 & 0.428371 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263726&T=2

[TABLE]
[ROW][C]Multiple Linear Regression - Ordinary Least Squares[/C][/ROW]
[ROW][C]Variable[/C][C]Parameter[/C][C]S.D.[/C][C]T-STATH0: parameter = 0[/C][C]2-tail p-value[/C][C]1-tail p-value[/C][/ROW]
[ROW][C](Intercept)[/C][C]10.8218[/C][C]1.4759[/C][C]7.332[/C][C]2.57596e-12[/C][C]1.28798e-12[/C][/ROW]
[ROW][C]AMS.I[/C][C]0.0460526[/C][C]0.0140601[/C][C]3.275[/C][C]0.00119141[/C][C]0.000595705[/C][/ROW]
[ROW][C]AMS.E[/C][C]-0.0322419[/C][C]0.0184581[/C][C]-1.747[/C][C]0.0818032[/C][C]0.0409016[/C][/ROW]
[ROW][C]AMS.A[/C][C]-0.0812149[/C][C]0.0413841[/C][C]-1.962[/C][C]0.0507239[/C][C]0.0253619[/C][/ROW]
[ROW][C]TOT[/C][C]0.00721696[/C][C]0.0399401[/C][C]0.1807[/C][C]0.856741[/C][C]0.428371[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263726&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263726&T=2

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Ordinary Least Squares
VariableParameterS.D.T-STATH0: parameter = 02-tail p-value1-tail p-value
(Intercept)10.82181.47597.3322.57596e-121.28798e-12
AMS.I0.04605260.01406013.2750.001191410.000595705
AMS.E-0.03224190.0184581-1.7470.08180320.0409016
AMS.A-0.08121490.0413841-1.9620.05072390.0253619
TOT0.007216960.03994010.18070.8567410.428371






Multiple Linear Regression - Regression Statistics
Multiple R0.240058
R-squared0.0576279
Adjusted R-squared0.0438203
F-TEST (value)4.17362
F-TEST (DF numerator)4
F-TEST (DF denominator)273
p-value0.00268594
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.23675
Sum Squared Residuals1365.83

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Regression Statistics \tabularnewline
Multiple R & 0.240058 \tabularnewline
R-squared & 0.0576279 \tabularnewline
Adjusted R-squared & 0.0438203 \tabularnewline
F-TEST (value) & 4.17362 \tabularnewline
F-TEST (DF numerator) & 4 \tabularnewline
F-TEST (DF denominator) & 273 \tabularnewline
p-value & 0.00268594 \tabularnewline
Multiple Linear Regression - Residual Statistics \tabularnewline
Residual Standard Deviation & 2.23675 \tabularnewline
Sum Squared Residuals & 1365.83 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263726&T=3

[TABLE]
[ROW][C]Multiple Linear Regression - Regression Statistics[/C][/ROW]
[ROW][C]Multiple R[/C][C]0.240058[/C][/ROW]
[ROW][C]R-squared[/C][C]0.0576279[/C][/ROW]
[ROW][C]Adjusted R-squared[/C][C]0.0438203[/C][/ROW]
[ROW][C]F-TEST (value)[/C][C]4.17362[/C][/ROW]
[ROW][C]F-TEST (DF numerator)[/C][C]4[/C][/ROW]
[ROW][C]F-TEST (DF denominator)[/C][C]273[/C][/ROW]
[ROW][C]p-value[/C][C]0.00268594[/C][/ROW]
[ROW][C]Multiple Linear Regression - Residual Statistics[/C][/ROW]
[ROW][C]Residual Standard Deviation[/C][C]2.23675[/C][/ROW]
[ROW][C]Sum Squared Residuals[/C][C]1365.83[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263726&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263726&T=3

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Regression Statistics
Multiple R0.240058
R-squared0.0576279
Adjusted R-squared0.0438203
F-TEST (value)4.17362
F-TEST (DF numerator)4
F-TEST (DF denominator)273
p-value0.00268594
Multiple Linear Regression - Residual Statistics
Residual Standard Deviation2.23675
Sum Squared Residuals1365.83






Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11210.17531.82468
2811.211-3.211
31110.4710.529002
41311.34671.65329
51110.78450.215495
61010.4808-0.480822
7710.32-3.31998
81010.3281-0.328116
91511.73723.26284
101212.2875-0.287495
111210.54541.45459
121011.6711-1.6711
131010.1285-0.128458
141410.90093.09905
15611.2559-5.25585
161210.54381.45616
171410.43513.56487
181110.88610.113918
19811.016-3.01599
201211.2030.797011
211511.24743.75262
221310.94832.05169
231110.87560.124445
241210.90011.09987
25710.8842-3.88418
261110.75950.240529
27710.802-3.80205
281210.48831.5117
291211.35560.644442
301310.57032.42965
3199.3918-0.3918
321110.4840.516003
331210.66791.33211
341510.24134.75869
351210.30951.69046
36610.9319-4.93186
37510.8019-5.80192
381310.6982.302
391111.2596-0.259603
40610.2962-4.2962
411210.6591.341
421010.8875-0.887478
43610.701-4.70095
44129.736352.26365
45119.627931.37207
46611.5499-5.54987
471210.69281.30723
481211.13850.861517
49811.2237-3.22375
501010.719-0.718953
511110.74150.258529
52710.4918-3.49184
531210.62141.37864
541311.31611.68386
551411.4172.58304
561210.93791.06209
5769.76446-3.76446
581410.30933.69069
591010.5958-0.595815
601210.77221.22778
611111.3098-0.309796
621010.828-0.827961
6379.12845-2.12845
641210.5441.45601
65710.5823-3.58233
661210.18391.81613
671210.9381.06199
681011.2951-1.29507
691010.5108-0.510837
701210.22551.77454
711210.62611.37394
721210.86441.13557
73810.7176-2.7176
741011.8362-1.83624
7559.77696-4.77696
761010.1211-0.121129
77108.35441.6456
781212.5037-0.503721
791111.9417-0.941739
8097.704131.29587
811211.70130.298658
821111.7729-0.772893
83108.510781.48922
841212.7935-0.793483
851011.0238-1.02383
8698.946040.053964
871110.2130.787028
881215.9657-3.96567
8976.701870.298131
90119.72541.2746
911216.6588-4.65876
9266.43893-0.438927
9395.391153.60885
941514.12630.873728
95109.747320.252682
961110.35830.641747
971210.80011.1999
981210.60571.3943
991211.46580.53417
1001113.1154-2.11543
10198.939320.0606825
1021110.16040.839627
103129.480562.51944
104129.054032.94597
1051416.834-2.83396
10688.63209-0.632094
1071011.7377-1.73771
10899.48129-0.481286
1091012.0971-2.09712
110910.1462-1.14618
111109.257290.742709
1121212.2583-0.258303
1131113.1163-2.11631
11497.51991.4801
115119.260931.73907
1161210.89881.10119
1171216.1737-4.1737
11875.259441.74056
1191211.14970.850313
1201211.32070.679341
1211212.8912-0.891233
122105.892314.10769
1231515.897-0.897045
124106.238183.76182
1251515.9047-0.904705
126105.847114.15289
1271516.0107-1.01069
12894.986224.01378
1291514.660.340036
130129.672512.32749
1311311.30911.6909
1321210.94061.05943
1331214.5846-2.58461
134810.2481-2.24814
13594.139784.86022
1361514.7070.292986
1371210.74161.25841
138127.756684.24332
1391514.89520.104758
1401110.45320.546843
1411214.7518-2.75177
14262.532593.46741
1431413.10610.893879
1441210.40631.59375
1451210.95541.04461
1461211.72120.278768
1471111.2804-0.280363
1481211.06070.939264
1491211.00380.99624
1501210.65231.34773
1511214.622-2.62201
152811.1756-3.17564
15387.191880.808122
1541210.05181.94819
1551212.6428-0.642793
1561112.6529-1.65289
1571010.9476-0.947582
158119.772041.22796
1591210.63251.36751
1601311.29591.70411
1611210.55491.44515
1621213.0581-1.05806
1631010.7306-0.730593
1641010.5201-0.520081
1651114.0356-3.03557
16685.613632.38637
1671213.5088-1.50875
16897.851351.14865
1691214.6779-2.67792
17098.627120.372881
171117.878133.12187
1721517.49-2.48997
173810.7941-2.79414
17487.992150.00785145
1751110.92770.0723353
1761110.51640.483573
177118.659612.34039
1781315.7871-2.78711
17975.740961.25904
1801214.0395-2.03945
181810.6202-2.62018
182814.4421-6.44207
18343.791030.208971
1841111.9566-0.956644
1851012.3095-2.30953
18675.797911.20209
1871211.88350.116476
1881112.9788-1.97878
18999.95191-0.951911
1901012.5448-2.54483
191810.6911-2.69107
19288.03183-0.031829
1931110.41330.586692
1941213.2041-1.20406
1951010.5718-0.571797
196108.498021.50198
1971214.4925-2.49251
19887.404160.595837
1991113.7055-2.70547
20089.59022-1.59022
201106.23863.7614
2021416.8843-2.88432
203911.0737-2.0737
20499.37928-0.379278
205107.309322.69068
2061311.35791.64211
207129.811762.18824
2081315.1409-2.14092
209815.3542-7.35423
21035.37105-2.37105
21186.774231.22577
2121211.86160.138382
2131112.9601-1.96009
21497.610241.38976
2151210.77581.22425
2161210.64691.35309
2171212.1371-0.137128
218108.088111.91189
2191314.2275-1.2275
22097.862861.13714
2211211.78120.218765
222117.334943.66506
2231414.0434-0.0433819
2241112.1738-1.17378
22597.565561.43444
2261213.6841-1.68409
22784.306233.69377
2281514.09440.905593
229129.09912.9009
2301412.74171.25831
2311214.369-2.36901
232910.8681-1.8681
23397.097671.90233
2341310.53872.46134
235138.892154.10785
2361515.0713-0.0712929
2371114.4829-3.4829
23877.62323-0.623225
239109.977280.0227188
240118.273952.72605
2411411.63832.36166
2421411.17352.82647
2431312.1660.833999
2441213.9604-1.96043
24585.596342.40366
2461314.7124-1.71245
24797.766441.23356
248128.739843.26016
2491313.2408-0.240794
2501111.2209-0.220947
251118.726542.27346
2521311.6261.37403
2531210.50221.49782
2541210.46671.53329
2551010.4101-0.41007
256910.2077-1.2077
257107.746652.25335
2581310.73682.26325
2591314.3012-1.30118
26098.633290.366705
261119.578711.42129
2621214.687-2.68702
26385.911682.08832
2641210.9091.09103
2651210.8811.11904
2661213.8961-1.89607
26797.611191.38881
2681211.53090.469098
2691212.4978-0.497821
2701110.09310.90691
2711216.9389-4.93893
27269.33133-3.33133
27377.80067-0.800672
274109.071410.928588
2751213.2741-1.27408
276108.774111.22589
2771213.6281-1.62808
278915.6387-6.63869
2793NANA

\begin{tabular}{lllllllll}
\hline
Multiple Linear Regression - Actuals, Interpolation, and Residuals \tabularnewline
Time or Index & Actuals & InterpolationForecast & ResidualsPrediction Error \tabularnewline
1 & 12 & 10.1753 & 1.82468 \tabularnewline
2 & 8 & 11.211 & -3.211 \tabularnewline
3 & 11 & 10.471 & 0.529002 \tabularnewline
4 & 13 & 11.3467 & 1.65329 \tabularnewline
5 & 11 & 10.7845 & 0.215495 \tabularnewline
6 & 10 & 10.4808 & -0.480822 \tabularnewline
7 & 7 & 10.32 & -3.31998 \tabularnewline
8 & 10 & 10.3281 & -0.328116 \tabularnewline
9 & 15 & 11.7372 & 3.26284 \tabularnewline
10 & 12 & 12.2875 & -0.287495 \tabularnewline
11 & 12 & 10.5454 & 1.45459 \tabularnewline
12 & 10 & 11.6711 & -1.6711 \tabularnewline
13 & 10 & 10.1285 & -0.128458 \tabularnewline
14 & 14 & 10.9009 & 3.09905 \tabularnewline
15 & 6 & 11.2559 & -5.25585 \tabularnewline
16 & 12 & 10.5438 & 1.45616 \tabularnewline
17 & 14 & 10.4351 & 3.56487 \tabularnewline
18 & 11 & 10.8861 & 0.113918 \tabularnewline
19 & 8 & 11.016 & -3.01599 \tabularnewline
20 & 12 & 11.203 & 0.797011 \tabularnewline
21 & 15 & 11.2474 & 3.75262 \tabularnewline
22 & 13 & 10.9483 & 2.05169 \tabularnewline
23 & 11 & 10.8756 & 0.124445 \tabularnewline
24 & 12 & 10.9001 & 1.09987 \tabularnewline
25 & 7 & 10.8842 & -3.88418 \tabularnewline
26 & 11 & 10.7595 & 0.240529 \tabularnewline
27 & 7 & 10.802 & -3.80205 \tabularnewline
28 & 12 & 10.4883 & 1.5117 \tabularnewline
29 & 12 & 11.3556 & 0.644442 \tabularnewline
30 & 13 & 10.5703 & 2.42965 \tabularnewline
31 & 9 & 9.3918 & -0.3918 \tabularnewline
32 & 11 & 10.484 & 0.516003 \tabularnewline
33 & 12 & 10.6679 & 1.33211 \tabularnewline
34 & 15 & 10.2413 & 4.75869 \tabularnewline
35 & 12 & 10.3095 & 1.69046 \tabularnewline
36 & 6 & 10.9319 & -4.93186 \tabularnewline
37 & 5 & 10.8019 & -5.80192 \tabularnewline
38 & 13 & 10.698 & 2.302 \tabularnewline
39 & 11 & 11.2596 & -0.259603 \tabularnewline
40 & 6 & 10.2962 & -4.2962 \tabularnewline
41 & 12 & 10.659 & 1.341 \tabularnewline
42 & 10 & 10.8875 & -0.887478 \tabularnewline
43 & 6 & 10.701 & -4.70095 \tabularnewline
44 & 12 & 9.73635 & 2.26365 \tabularnewline
45 & 11 & 9.62793 & 1.37207 \tabularnewline
46 & 6 & 11.5499 & -5.54987 \tabularnewline
47 & 12 & 10.6928 & 1.30723 \tabularnewline
48 & 12 & 11.1385 & 0.861517 \tabularnewline
49 & 8 & 11.2237 & -3.22375 \tabularnewline
50 & 10 & 10.719 & -0.718953 \tabularnewline
51 & 11 & 10.7415 & 0.258529 \tabularnewline
52 & 7 & 10.4918 & -3.49184 \tabularnewline
53 & 12 & 10.6214 & 1.37864 \tabularnewline
54 & 13 & 11.3161 & 1.68386 \tabularnewline
55 & 14 & 11.417 & 2.58304 \tabularnewline
56 & 12 & 10.9379 & 1.06209 \tabularnewline
57 & 6 & 9.76446 & -3.76446 \tabularnewline
58 & 14 & 10.3093 & 3.69069 \tabularnewline
59 & 10 & 10.5958 & -0.595815 \tabularnewline
60 & 12 & 10.7722 & 1.22778 \tabularnewline
61 & 11 & 11.3098 & -0.309796 \tabularnewline
62 & 10 & 10.828 & -0.827961 \tabularnewline
63 & 7 & 9.12845 & -2.12845 \tabularnewline
64 & 12 & 10.544 & 1.45601 \tabularnewline
65 & 7 & 10.5823 & -3.58233 \tabularnewline
66 & 12 & 10.1839 & 1.81613 \tabularnewline
67 & 12 & 10.938 & 1.06199 \tabularnewline
68 & 10 & 11.2951 & -1.29507 \tabularnewline
69 & 10 & 10.5108 & -0.510837 \tabularnewline
70 & 12 & 10.2255 & 1.77454 \tabularnewline
71 & 12 & 10.6261 & 1.37394 \tabularnewline
72 & 12 & 10.8644 & 1.13557 \tabularnewline
73 & 8 & 10.7176 & -2.7176 \tabularnewline
74 & 10 & 11.8362 & -1.83624 \tabularnewline
75 & 5 & 9.77696 & -4.77696 \tabularnewline
76 & 10 & 10.1211 & -0.121129 \tabularnewline
77 & 10 & 8.3544 & 1.6456 \tabularnewline
78 & 12 & 12.5037 & -0.503721 \tabularnewline
79 & 11 & 11.9417 & -0.941739 \tabularnewline
80 & 9 & 7.70413 & 1.29587 \tabularnewline
81 & 12 & 11.7013 & 0.298658 \tabularnewline
82 & 11 & 11.7729 & -0.772893 \tabularnewline
83 & 10 & 8.51078 & 1.48922 \tabularnewline
84 & 12 & 12.7935 & -0.793483 \tabularnewline
85 & 10 & 11.0238 & -1.02383 \tabularnewline
86 & 9 & 8.94604 & 0.053964 \tabularnewline
87 & 11 & 10.213 & 0.787028 \tabularnewline
88 & 12 & 15.9657 & -3.96567 \tabularnewline
89 & 7 & 6.70187 & 0.298131 \tabularnewline
90 & 11 & 9.7254 & 1.2746 \tabularnewline
91 & 12 & 16.6588 & -4.65876 \tabularnewline
92 & 6 & 6.43893 & -0.438927 \tabularnewline
93 & 9 & 5.39115 & 3.60885 \tabularnewline
94 & 15 & 14.1263 & 0.873728 \tabularnewline
95 & 10 & 9.74732 & 0.252682 \tabularnewline
96 & 11 & 10.3583 & 0.641747 \tabularnewline
97 & 12 & 10.8001 & 1.1999 \tabularnewline
98 & 12 & 10.6057 & 1.3943 \tabularnewline
99 & 12 & 11.4658 & 0.53417 \tabularnewline
100 & 11 & 13.1154 & -2.11543 \tabularnewline
101 & 9 & 8.93932 & 0.0606825 \tabularnewline
102 & 11 & 10.1604 & 0.839627 \tabularnewline
103 & 12 & 9.48056 & 2.51944 \tabularnewline
104 & 12 & 9.05403 & 2.94597 \tabularnewline
105 & 14 & 16.834 & -2.83396 \tabularnewline
106 & 8 & 8.63209 & -0.632094 \tabularnewline
107 & 10 & 11.7377 & -1.73771 \tabularnewline
108 & 9 & 9.48129 & -0.481286 \tabularnewline
109 & 10 & 12.0971 & -2.09712 \tabularnewline
110 & 9 & 10.1462 & -1.14618 \tabularnewline
111 & 10 & 9.25729 & 0.742709 \tabularnewline
112 & 12 & 12.2583 & -0.258303 \tabularnewline
113 & 11 & 13.1163 & -2.11631 \tabularnewline
114 & 9 & 7.5199 & 1.4801 \tabularnewline
115 & 11 & 9.26093 & 1.73907 \tabularnewline
116 & 12 & 10.8988 & 1.10119 \tabularnewline
117 & 12 & 16.1737 & -4.1737 \tabularnewline
118 & 7 & 5.25944 & 1.74056 \tabularnewline
119 & 12 & 11.1497 & 0.850313 \tabularnewline
120 & 12 & 11.3207 & 0.679341 \tabularnewline
121 & 12 & 12.8912 & -0.891233 \tabularnewline
122 & 10 & 5.89231 & 4.10769 \tabularnewline
123 & 15 & 15.897 & -0.897045 \tabularnewline
124 & 10 & 6.23818 & 3.76182 \tabularnewline
125 & 15 & 15.9047 & -0.904705 \tabularnewline
126 & 10 & 5.84711 & 4.15289 \tabularnewline
127 & 15 & 16.0107 & -1.01069 \tabularnewline
128 & 9 & 4.98622 & 4.01378 \tabularnewline
129 & 15 & 14.66 & 0.340036 \tabularnewline
130 & 12 & 9.67251 & 2.32749 \tabularnewline
131 & 13 & 11.3091 & 1.6909 \tabularnewline
132 & 12 & 10.9406 & 1.05943 \tabularnewline
133 & 12 & 14.5846 & -2.58461 \tabularnewline
134 & 8 & 10.2481 & -2.24814 \tabularnewline
135 & 9 & 4.13978 & 4.86022 \tabularnewline
136 & 15 & 14.707 & 0.292986 \tabularnewline
137 & 12 & 10.7416 & 1.25841 \tabularnewline
138 & 12 & 7.75668 & 4.24332 \tabularnewline
139 & 15 & 14.8952 & 0.104758 \tabularnewline
140 & 11 & 10.4532 & 0.546843 \tabularnewline
141 & 12 & 14.7518 & -2.75177 \tabularnewline
142 & 6 & 2.53259 & 3.46741 \tabularnewline
143 & 14 & 13.1061 & 0.893879 \tabularnewline
144 & 12 & 10.4063 & 1.59375 \tabularnewline
145 & 12 & 10.9554 & 1.04461 \tabularnewline
146 & 12 & 11.7212 & 0.278768 \tabularnewline
147 & 11 & 11.2804 & -0.280363 \tabularnewline
148 & 12 & 11.0607 & 0.939264 \tabularnewline
149 & 12 & 11.0038 & 0.99624 \tabularnewline
150 & 12 & 10.6523 & 1.34773 \tabularnewline
151 & 12 & 14.622 & -2.62201 \tabularnewline
152 & 8 & 11.1756 & -3.17564 \tabularnewline
153 & 8 & 7.19188 & 0.808122 \tabularnewline
154 & 12 & 10.0518 & 1.94819 \tabularnewline
155 & 12 & 12.6428 & -0.642793 \tabularnewline
156 & 11 & 12.6529 & -1.65289 \tabularnewline
157 & 10 & 10.9476 & -0.947582 \tabularnewline
158 & 11 & 9.77204 & 1.22796 \tabularnewline
159 & 12 & 10.6325 & 1.36751 \tabularnewline
160 & 13 & 11.2959 & 1.70411 \tabularnewline
161 & 12 & 10.5549 & 1.44515 \tabularnewline
162 & 12 & 13.0581 & -1.05806 \tabularnewline
163 & 10 & 10.7306 & -0.730593 \tabularnewline
164 & 10 & 10.5201 & -0.520081 \tabularnewline
165 & 11 & 14.0356 & -3.03557 \tabularnewline
166 & 8 & 5.61363 & 2.38637 \tabularnewline
167 & 12 & 13.5088 & -1.50875 \tabularnewline
168 & 9 & 7.85135 & 1.14865 \tabularnewline
169 & 12 & 14.6779 & -2.67792 \tabularnewline
170 & 9 & 8.62712 & 0.372881 \tabularnewline
171 & 11 & 7.87813 & 3.12187 \tabularnewline
172 & 15 & 17.49 & -2.48997 \tabularnewline
173 & 8 & 10.7941 & -2.79414 \tabularnewline
174 & 8 & 7.99215 & 0.00785145 \tabularnewline
175 & 11 & 10.9277 & 0.0723353 \tabularnewline
176 & 11 & 10.5164 & 0.483573 \tabularnewline
177 & 11 & 8.65961 & 2.34039 \tabularnewline
178 & 13 & 15.7871 & -2.78711 \tabularnewline
179 & 7 & 5.74096 & 1.25904 \tabularnewline
180 & 12 & 14.0395 & -2.03945 \tabularnewline
181 & 8 & 10.6202 & -2.62018 \tabularnewline
182 & 8 & 14.4421 & -6.44207 \tabularnewline
183 & 4 & 3.79103 & 0.208971 \tabularnewline
184 & 11 & 11.9566 & -0.956644 \tabularnewline
185 & 10 & 12.3095 & -2.30953 \tabularnewline
186 & 7 & 5.79791 & 1.20209 \tabularnewline
187 & 12 & 11.8835 & 0.116476 \tabularnewline
188 & 11 & 12.9788 & -1.97878 \tabularnewline
189 & 9 & 9.95191 & -0.951911 \tabularnewline
190 & 10 & 12.5448 & -2.54483 \tabularnewline
191 & 8 & 10.6911 & -2.69107 \tabularnewline
192 & 8 & 8.03183 & -0.031829 \tabularnewline
193 & 11 & 10.4133 & 0.586692 \tabularnewline
194 & 12 & 13.2041 & -1.20406 \tabularnewline
195 & 10 & 10.5718 & -0.571797 \tabularnewline
196 & 10 & 8.49802 & 1.50198 \tabularnewline
197 & 12 & 14.4925 & -2.49251 \tabularnewline
198 & 8 & 7.40416 & 0.595837 \tabularnewline
199 & 11 & 13.7055 & -2.70547 \tabularnewline
200 & 8 & 9.59022 & -1.59022 \tabularnewline
201 & 10 & 6.2386 & 3.7614 \tabularnewline
202 & 14 & 16.8843 & -2.88432 \tabularnewline
203 & 9 & 11.0737 & -2.0737 \tabularnewline
204 & 9 & 9.37928 & -0.379278 \tabularnewline
205 & 10 & 7.30932 & 2.69068 \tabularnewline
206 & 13 & 11.3579 & 1.64211 \tabularnewline
207 & 12 & 9.81176 & 2.18824 \tabularnewline
208 & 13 & 15.1409 & -2.14092 \tabularnewline
209 & 8 & 15.3542 & -7.35423 \tabularnewline
210 & 3 & 5.37105 & -2.37105 \tabularnewline
211 & 8 & 6.77423 & 1.22577 \tabularnewline
212 & 12 & 11.8616 & 0.138382 \tabularnewline
213 & 11 & 12.9601 & -1.96009 \tabularnewline
214 & 9 & 7.61024 & 1.38976 \tabularnewline
215 & 12 & 10.7758 & 1.22425 \tabularnewline
216 & 12 & 10.6469 & 1.35309 \tabularnewline
217 & 12 & 12.1371 & -0.137128 \tabularnewline
218 & 10 & 8.08811 & 1.91189 \tabularnewline
219 & 13 & 14.2275 & -1.2275 \tabularnewline
220 & 9 & 7.86286 & 1.13714 \tabularnewline
221 & 12 & 11.7812 & 0.218765 \tabularnewline
222 & 11 & 7.33494 & 3.66506 \tabularnewline
223 & 14 & 14.0434 & -0.0433819 \tabularnewline
224 & 11 & 12.1738 & -1.17378 \tabularnewline
225 & 9 & 7.56556 & 1.43444 \tabularnewline
226 & 12 & 13.6841 & -1.68409 \tabularnewline
227 & 8 & 4.30623 & 3.69377 \tabularnewline
228 & 15 & 14.0944 & 0.905593 \tabularnewline
229 & 12 & 9.0991 & 2.9009 \tabularnewline
230 & 14 & 12.7417 & 1.25831 \tabularnewline
231 & 12 & 14.369 & -2.36901 \tabularnewline
232 & 9 & 10.8681 & -1.8681 \tabularnewline
233 & 9 & 7.09767 & 1.90233 \tabularnewline
234 & 13 & 10.5387 & 2.46134 \tabularnewline
235 & 13 & 8.89215 & 4.10785 \tabularnewline
236 & 15 & 15.0713 & -0.0712929 \tabularnewline
237 & 11 & 14.4829 & -3.4829 \tabularnewline
238 & 7 & 7.62323 & -0.623225 \tabularnewline
239 & 10 & 9.97728 & 0.0227188 \tabularnewline
240 & 11 & 8.27395 & 2.72605 \tabularnewline
241 & 14 & 11.6383 & 2.36166 \tabularnewline
242 & 14 & 11.1735 & 2.82647 \tabularnewline
243 & 13 & 12.166 & 0.833999 \tabularnewline
244 & 12 & 13.9604 & -1.96043 \tabularnewline
245 & 8 & 5.59634 & 2.40366 \tabularnewline
246 & 13 & 14.7124 & -1.71245 \tabularnewline
247 & 9 & 7.76644 & 1.23356 \tabularnewline
248 & 12 & 8.73984 & 3.26016 \tabularnewline
249 & 13 & 13.2408 & -0.240794 \tabularnewline
250 & 11 & 11.2209 & -0.220947 \tabularnewline
251 & 11 & 8.72654 & 2.27346 \tabularnewline
252 & 13 & 11.626 & 1.37403 \tabularnewline
253 & 12 & 10.5022 & 1.49782 \tabularnewline
254 & 12 & 10.4667 & 1.53329 \tabularnewline
255 & 10 & 10.4101 & -0.41007 \tabularnewline
256 & 9 & 10.2077 & -1.2077 \tabularnewline
257 & 10 & 7.74665 & 2.25335 \tabularnewline
258 & 13 & 10.7368 & 2.26325 \tabularnewline
259 & 13 & 14.3012 & -1.30118 \tabularnewline
260 & 9 & 8.63329 & 0.366705 \tabularnewline
261 & 11 & 9.57871 & 1.42129 \tabularnewline
262 & 12 & 14.687 & -2.68702 \tabularnewline
263 & 8 & 5.91168 & 2.08832 \tabularnewline
264 & 12 & 10.909 & 1.09103 \tabularnewline
265 & 12 & 10.881 & 1.11904 \tabularnewline
266 & 12 & 13.8961 & -1.89607 \tabularnewline
267 & 9 & 7.61119 & 1.38881 \tabularnewline
268 & 12 & 11.5309 & 0.469098 \tabularnewline
269 & 12 & 12.4978 & -0.497821 \tabularnewline
270 & 11 & 10.0931 & 0.90691 \tabularnewline
271 & 12 & 16.9389 & -4.93893 \tabularnewline
272 & 6 & 9.33133 & -3.33133 \tabularnewline
273 & 7 & 7.80067 & -0.800672 \tabularnewline
274 & 10 & 9.07141 & 0.928588 \tabularnewline
275 & 12 & 13.2741 & -1.27408 \tabularnewline
276 & 10 & 8.77411 & 1.22589 \tabularnewline
277 & 12 & 13.6281 & -1.62808 \tabularnewline
278 & 9 & 15.6387 & -6.63869 \tabularnewline
279 & 3 & NA & NA \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263726&T=4

[TABLE]
[ROW][C]Multiple Linear Regression - Actuals, Interpolation, and Residuals[/C][/ROW]
[ROW][C]Time or Index[/C][C]Actuals[/C][C]InterpolationForecast[/C][C]ResidualsPrediction Error[/C][/ROW]
[ROW][C]1[/C][C]12[/C][C]10.1753[/C][C]1.82468[/C][/ROW]
[ROW][C]2[/C][C]8[/C][C]11.211[/C][C]-3.211[/C][/ROW]
[ROW][C]3[/C][C]11[/C][C]10.471[/C][C]0.529002[/C][/ROW]
[ROW][C]4[/C][C]13[/C][C]11.3467[/C][C]1.65329[/C][/ROW]
[ROW][C]5[/C][C]11[/C][C]10.7845[/C][C]0.215495[/C][/ROW]
[ROW][C]6[/C][C]10[/C][C]10.4808[/C][C]-0.480822[/C][/ROW]
[ROW][C]7[/C][C]7[/C][C]10.32[/C][C]-3.31998[/C][/ROW]
[ROW][C]8[/C][C]10[/C][C]10.3281[/C][C]-0.328116[/C][/ROW]
[ROW][C]9[/C][C]15[/C][C]11.7372[/C][C]3.26284[/C][/ROW]
[ROW][C]10[/C][C]12[/C][C]12.2875[/C][C]-0.287495[/C][/ROW]
[ROW][C]11[/C][C]12[/C][C]10.5454[/C][C]1.45459[/C][/ROW]
[ROW][C]12[/C][C]10[/C][C]11.6711[/C][C]-1.6711[/C][/ROW]
[ROW][C]13[/C][C]10[/C][C]10.1285[/C][C]-0.128458[/C][/ROW]
[ROW][C]14[/C][C]14[/C][C]10.9009[/C][C]3.09905[/C][/ROW]
[ROW][C]15[/C][C]6[/C][C]11.2559[/C][C]-5.25585[/C][/ROW]
[ROW][C]16[/C][C]12[/C][C]10.5438[/C][C]1.45616[/C][/ROW]
[ROW][C]17[/C][C]14[/C][C]10.4351[/C][C]3.56487[/C][/ROW]
[ROW][C]18[/C][C]11[/C][C]10.8861[/C][C]0.113918[/C][/ROW]
[ROW][C]19[/C][C]8[/C][C]11.016[/C][C]-3.01599[/C][/ROW]
[ROW][C]20[/C][C]12[/C][C]11.203[/C][C]0.797011[/C][/ROW]
[ROW][C]21[/C][C]15[/C][C]11.2474[/C][C]3.75262[/C][/ROW]
[ROW][C]22[/C][C]13[/C][C]10.9483[/C][C]2.05169[/C][/ROW]
[ROW][C]23[/C][C]11[/C][C]10.8756[/C][C]0.124445[/C][/ROW]
[ROW][C]24[/C][C]12[/C][C]10.9001[/C][C]1.09987[/C][/ROW]
[ROW][C]25[/C][C]7[/C][C]10.8842[/C][C]-3.88418[/C][/ROW]
[ROW][C]26[/C][C]11[/C][C]10.7595[/C][C]0.240529[/C][/ROW]
[ROW][C]27[/C][C]7[/C][C]10.802[/C][C]-3.80205[/C][/ROW]
[ROW][C]28[/C][C]12[/C][C]10.4883[/C][C]1.5117[/C][/ROW]
[ROW][C]29[/C][C]12[/C][C]11.3556[/C][C]0.644442[/C][/ROW]
[ROW][C]30[/C][C]13[/C][C]10.5703[/C][C]2.42965[/C][/ROW]
[ROW][C]31[/C][C]9[/C][C]9.3918[/C][C]-0.3918[/C][/ROW]
[ROW][C]32[/C][C]11[/C][C]10.484[/C][C]0.516003[/C][/ROW]
[ROW][C]33[/C][C]12[/C][C]10.6679[/C][C]1.33211[/C][/ROW]
[ROW][C]34[/C][C]15[/C][C]10.2413[/C][C]4.75869[/C][/ROW]
[ROW][C]35[/C][C]12[/C][C]10.3095[/C][C]1.69046[/C][/ROW]
[ROW][C]36[/C][C]6[/C][C]10.9319[/C][C]-4.93186[/C][/ROW]
[ROW][C]37[/C][C]5[/C][C]10.8019[/C][C]-5.80192[/C][/ROW]
[ROW][C]38[/C][C]13[/C][C]10.698[/C][C]2.302[/C][/ROW]
[ROW][C]39[/C][C]11[/C][C]11.2596[/C][C]-0.259603[/C][/ROW]
[ROW][C]40[/C][C]6[/C][C]10.2962[/C][C]-4.2962[/C][/ROW]
[ROW][C]41[/C][C]12[/C][C]10.659[/C][C]1.341[/C][/ROW]
[ROW][C]42[/C][C]10[/C][C]10.8875[/C][C]-0.887478[/C][/ROW]
[ROW][C]43[/C][C]6[/C][C]10.701[/C][C]-4.70095[/C][/ROW]
[ROW][C]44[/C][C]12[/C][C]9.73635[/C][C]2.26365[/C][/ROW]
[ROW][C]45[/C][C]11[/C][C]9.62793[/C][C]1.37207[/C][/ROW]
[ROW][C]46[/C][C]6[/C][C]11.5499[/C][C]-5.54987[/C][/ROW]
[ROW][C]47[/C][C]12[/C][C]10.6928[/C][C]1.30723[/C][/ROW]
[ROW][C]48[/C][C]12[/C][C]11.1385[/C][C]0.861517[/C][/ROW]
[ROW][C]49[/C][C]8[/C][C]11.2237[/C][C]-3.22375[/C][/ROW]
[ROW][C]50[/C][C]10[/C][C]10.719[/C][C]-0.718953[/C][/ROW]
[ROW][C]51[/C][C]11[/C][C]10.7415[/C][C]0.258529[/C][/ROW]
[ROW][C]52[/C][C]7[/C][C]10.4918[/C][C]-3.49184[/C][/ROW]
[ROW][C]53[/C][C]12[/C][C]10.6214[/C][C]1.37864[/C][/ROW]
[ROW][C]54[/C][C]13[/C][C]11.3161[/C][C]1.68386[/C][/ROW]
[ROW][C]55[/C][C]14[/C][C]11.417[/C][C]2.58304[/C][/ROW]
[ROW][C]56[/C][C]12[/C][C]10.9379[/C][C]1.06209[/C][/ROW]
[ROW][C]57[/C][C]6[/C][C]9.76446[/C][C]-3.76446[/C][/ROW]
[ROW][C]58[/C][C]14[/C][C]10.3093[/C][C]3.69069[/C][/ROW]
[ROW][C]59[/C][C]10[/C][C]10.5958[/C][C]-0.595815[/C][/ROW]
[ROW][C]60[/C][C]12[/C][C]10.7722[/C][C]1.22778[/C][/ROW]
[ROW][C]61[/C][C]11[/C][C]11.3098[/C][C]-0.309796[/C][/ROW]
[ROW][C]62[/C][C]10[/C][C]10.828[/C][C]-0.827961[/C][/ROW]
[ROW][C]63[/C][C]7[/C][C]9.12845[/C][C]-2.12845[/C][/ROW]
[ROW][C]64[/C][C]12[/C][C]10.544[/C][C]1.45601[/C][/ROW]
[ROW][C]65[/C][C]7[/C][C]10.5823[/C][C]-3.58233[/C][/ROW]
[ROW][C]66[/C][C]12[/C][C]10.1839[/C][C]1.81613[/C][/ROW]
[ROW][C]67[/C][C]12[/C][C]10.938[/C][C]1.06199[/C][/ROW]
[ROW][C]68[/C][C]10[/C][C]11.2951[/C][C]-1.29507[/C][/ROW]
[ROW][C]69[/C][C]10[/C][C]10.5108[/C][C]-0.510837[/C][/ROW]
[ROW][C]70[/C][C]12[/C][C]10.2255[/C][C]1.77454[/C][/ROW]
[ROW][C]71[/C][C]12[/C][C]10.6261[/C][C]1.37394[/C][/ROW]
[ROW][C]72[/C][C]12[/C][C]10.8644[/C][C]1.13557[/C][/ROW]
[ROW][C]73[/C][C]8[/C][C]10.7176[/C][C]-2.7176[/C][/ROW]
[ROW][C]74[/C][C]10[/C][C]11.8362[/C][C]-1.83624[/C][/ROW]
[ROW][C]75[/C][C]5[/C][C]9.77696[/C][C]-4.77696[/C][/ROW]
[ROW][C]76[/C][C]10[/C][C]10.1211[/C][C]-0.121129[/C][/ROW]
[ROW][C]77[/C][C]10[/C][C]8.3544[/C][C]1.6456[/C][/ROW]
[ROW][C]78[/C][C]12[/C][C]12.5037[/C][C]-0.503721[/C][/ROW]
[ROW][C]79[/C][C]11[/C][C]11.9417[/C][C]-0.941739[/C][/ROW]
[ROW][C]80[/C][C]9[/C][C]7.70413[/C][C]1.29587[/C][/ROW]
[ROW][C]81[/C][C]12[/C][C]11.7013[/C][C]0.298658[/C][/ROW]
[ROW][C]82[/C][C]11[/C][C]11.7729[/C][C]-0.772893[/C][/ROW]
[ROW][C]83[/C][C]10[/C][C]8.51078[/C][C]1.48922[/C][/ROW]
[ROW][C]84[/C][C]12[/C][C]12.7935[/C][C]-0.793483[/C][/ROW]
[ROW][C]85[/C][C]10[/C][C]11.0238[/C][C]-1.02383[/C][/ROW]
[ROW][C]86[/C][C]9[/C][C]8.94604[/C][C]0.053964[/C][/ROW]
[ROW][C]87[/C][C]11[/C][C]10.213[/C][C]0.787028[/C][/ROW]
[ROW][C]88[/C][C]12[/C][C]15.9657[/C][C]-3.96567[/C][/ROW]
[ROW][C]89[/C][C]7[/C][C]6.70187[/C][C]0.298131[/C][/ROW]
[ROW][C]90[/C][C]11[/C][C]9.7254[/C][C]1.2746[/C][/ROW]
[ROW][C]91[/C][C]12[/C][C]16.6588[/C][C]-4.65876[/C][/ROW]
[ROW][C]92[/C][C]6[/C][C]6.43893[/C][C]-0.438927[/C][/ROW]
[ROW][C]93[/C][C]9[/C][C]5.39115[/C][C]3.60885[/C][/ROW]
[ROW][C]94[/C][C]15[/C][C]14.1263[/C][C]0.873728[/C][/ROW]
[ROW][C]95[/C][C]10[/C][C]9.74732[/C][C]0.252682[/C][/ROW]
[ROW][C]96[/C][C]11[/C][C]10.3583[/C][C]0.641747[/C][/ROW]
[ROW][C]97[/C][C]12[/C][C]10.8001[/C][C]1.1999[/C][/ROW]
[ROW][C]98[/C][C]12[/C][C]10.6057[/C][C]1.3943[/C][/ROW]
[ROW][C]99[/C][C]12[/C][C]11.4658[/C][C]0.53417[/C][/ROW]
[ROW][C]100[/C][C]11[/C][C]13.1154[/C][C]-2.11543[/C][/ROW]
[ROW][C]101[/C][C]9[/C][C]8.93932[/C][C]0.0606825[/C][/ROW]
[ROW][C]102[/C][C]11[/C][C]10.1604[/C][C]0.839627[/C][/ROW]
[ROW][C]103[/C][C]12[/C][C]9.48056[/C][C]2.51944[/C][/ROW]
[ROW][C]104[/C][C]12[/C][C]9.05403[/C][C]2.94597[/C][/ROW]
[ROW][C]105[/C][C]14[/C][C]16.834[/C][C]-2.83396[/C][/ROW]
[ROW][C]106[/C][C]8[/C][C]8.63209[/C][C]-0.632094[/C][/ROW]
[ROW][C]107[/C][C]10[/C][C]11.7377[/C][C]-1.73771[/C][/ROW]
[ROW][C]108[/C][C]9[/C][C]9.48129[/C][C]-0.481286[/C][/ROW]
[ROW][C]109[/C][C]10[/C][C]12.0971[/C][C]-2.09712[/C][/ROW]
[ROW][C]110[/C][C]9[/C][C]10.1462[/C][C]-1.14618[/C][/ROW]
[ROW][C]111[/C][C]10[/C][C]9.25729[/C][C]0.742709[/C][/ROW]
[ROW][C]112[/C][C]12[/C][C]12.2583[/C][C]-0.258303[/C][/ROW]
[ROW][C]113[/C][C]11[/C][C]13.1163[/C][C]-2.11631[/C][/ROW]
[ROW][C]114[/C][C]9[/C][C]7.5199[/C][C]1.4801[/C][/ROW]
[ROW][C]115[/C][C]11[/C][C]9.26093[/C][C]1.73907[/C][/ROW]
[ROW][C]116[/C][C]12[/C][C]10.8988[/C][C]1.10119[/C][/ROW]
[ROW][C]117[/C][C]12[/C][C]16.1737[/C][C]-4.1737[/C][/ROW]
[ROW][C]118[/C][C]7[/C][C]5.25944[/C][C]1.74056[/C][/ROW]
[ROW][C]119[/C][C]12[/C][C]11.1497[/C][C]0.850313[/C][/ROW]
[ROW][C]120[/C][C]12[/C][C]11.3207[/C][C]0.679341[/C][/ROW]
[ROW][C]121[/C][C]12[/C][C]12.8912[/C][C]-0.891233[/C][/ROW]
[ROW][C]122[/C][C]10[/C][C]5.89231[/C][C]4.10769[/C][/ROW]
[ROW][C]123[/C][C]15[/C][C]15.897[/C][C]-0.897045[/C][/ROW]
[ROW][C]124[/C][C]10[/C][C]6.23818[/C][C]3.76182[/C][/ROW]
[ROW][C]125[/C][C]15[/C][C]15.9047[/C][C]-0.904705[/C][/ROW]
[ROW][C]126[/C][C]10[/C][C]5.84711[/C][C]4.15289[/C][/ROW]
[ROW][C]127[/C][C]15[/C][C]16.0107[/C][C]-1.01069[/C][/ROW]
[ROW][C]128[/C][C]9[/C][C]4.98622[/C][C]4.01378[/C][/ROW]
[ROW][C]129[/C][C]15[/C][C]14.66[/C][C]0.340036[/C][/ROW]
[ROW][C]130[/C][C]12[/C][C]9.67251[/C][C]2.32749[/C][/ROW]
[ROW][C]131[/C][C]13[/C][C]11.3091[/C][C]1.6909[/C][/ROW]
[ROW][C]132[/C][C]12[/C][C]10.9406[/C][C]1.05943[/C][/ROW]
[ROW][C]133[/C][C]12[/C][C]14.5846[/C][C]-2.58461[/C][/ROW]
[ROW][C]134[/C][C]8[/C][C]10.2481[/C][C]-2.24814[/C][/ROW]
[ROW][C]135[/C][C]9[/C][C]4.13978[/C][C]4.86022[/C][/ROW]
[ROW][C]136[/C][C]15[/C][C]14.707[/C][C]0.292986[/C][/ROW]
[ROW][C]137[/C][C]12[/C][C]10.7416[/C][C]1.25841[/C][/ROW]
[ROW][C]138[/C][C]12[/C][C]7.75668[/C][C]4.24332[/C][/ROW]
[ROW][C]139[/C][C]15[/C][C]14.8952[/C][C]0.104758[/C][/ROW]
[ROW][C]140[/C][C]11[/C][C]10.4532[/C][C]0.546843[/C][/ROW]
[ROW][C]141[/C][C]12[/C][C]14.7518[/C][C]-2.75177[/C][/ROW]
[ROW][C]142[/C][C]6[/C][C]2.53259[/C][C]3.46741[/C][/ROW]
[ROW][C]143[/C][C]14[/C][C]13.1061[/C][C]0.893879[/C][/ROW]
[ROW][C]144[/C][C]12[/C][C]10.4063[/C][C]1.59375[/C][/ROW]
[ROW][C]145[/C][C]12[/C][C]10.9554[/C][C]1.04461[/C][/ROW]
[ROW][C]146[/C][C]12[/C][C]11.7212[/C][C]0.278768[/C][/ROW]
[ROW][C]147[/C][C]11[/C][C]11.2804[/C][C]-0.280363[/C][/ROW]
[ROW][C]148[/C][C]12[/C][C]11.0607[/C][C]0.939264[/C][/ROW]
[ROW][C]149[/C][C]12[/C][C]11.0038[/C][C]0.99624[/C][/ROW]
[ROW][C]150[/C][C]12[/C][C]10.6523[/C][C]1.34773[/C][/ROW]
[ROW][C]151[/C][C]12[/C][C]14.622[/C][C]-2.62201[/C][/ROW]
[ROW][C]152[/C][C]8[/C][C]11.1756[/C][C]-3.17564[/C][/ROW]
[ROW][C]153[/C][C]8[/C][C]7.19188[/C][C]0.808122[/C][/ROW]
[ROW][C]154[/C][C]12[/C][C]10.0518[/C][C]1.94819[/C][/ROW]
[ROW][C]155[/C][C]12[/C][C]12.6428[/C][C]-0.642793[/C][/ROW]
[ROW][C]156[/C][C]11[/C][C]12.6529[/C][C]-1.65289[/C][/ROW]
[ROW][C]157[/C][C]10[/C][C]10.9476[/C][C]-0.947582[/C][/ROW]
[ROW][C]158[/C][C]11[/C][C]9.77204[/C][C]1.22796[/C][/ROW]
[ROW][C]159[/C][C]12[/C][C]10.6325[/C][C]1.36751[/C][/ROW]
[ROW][C]160[/C][C]13[/C][C]11.2959[/C][C]1.70411[/C][/ROW]
[ROW][C]161[/C][C]12[/C][C]10.5549[/C][C]1.44515[/C][/ROW]
[ROW][C]162[/C][C]12[/C][C]13.0581[/C][C]-1.05806[/C][/ROW]
[ROW][C]163[/C][C]10[/C][C]10.7306[/C][C]-0.730593[/C][/ROW]
[ROW][C]164[/C][C]10[/C][C]10.5201[/C][C]-0.520081[/C][/ROW]
[ROW][C]165[/C][C]11[/C][C]14.0356[/C][C]-3.03557[/C][/ROW]
[ROW][C]166[/C][C]8[/C][C]5.61363[/C][C]2.38637[/C][/ROW]
[ROW][C]167[/C][C]12[/C][C]13.5088[/C][C]-1.50875[/C][/ROW]
[ROW][C]168[/C][C]9[/C][C]7.85135[/C][C]1.14865[/C][/ROW]
[ROW][C]169[/C][C]12[/C][C]14.6779[/C][C]-2.67792[/C][/ROW]
[ROW][C]170[/C][C]9[/C][C]8.62712[/C][C]0.372881[/C][/ROW]
[ROW][C]171[/C][C]11[/C][C]7.87813[/C][C]3.12187[/C][/ROW]
[ROW][C]172[/C][C]15[/C][C]17.49[/C][C]-2.48997[/C][/ROW]
[ROW][C]173[/C][C]8[/C][C]10.7941[/C][C]-2.79414[/C][/ROW]
[ROW][C]174[/C][C]8[/C][C]7.99215[/C][C]0.00785145[/C][/ROW]
[ROW][C]175[/C][C]11[/C][C]10.9277[/C][C]0.0723353[/C][/ROW]
[ROW][C]176[/C][C]11[/C][C]10.5164[/C][C]0.483573[/C][/ROW]
[ROW][C]177[/C][C]11[/C][C]8.65961[/C][C]2.34039[/C][/ROW]
[ROW][C]178[/C][C]13[/C][C]15.7871[/C][C]-2.78711[/C][/ROW]
[ROW][C]179[/C][C]7[/C][C]5.74096[/C][C]1.25904[/C][/ROW]
[ROW][C]180[/C][C]12[/C][C]14.0395[/C][C]-2.03945[/C][/ROW]
[ROW][C]181[/C][C]8[/C][C]10.6202[/C][C]-2.62018[/C][/ROW]
[ROW][C]182[/C][C]8[/C][C]14.4421[/C][C]-6.44207[/C][/ROW]
[ROW][C]183[/C][C]4[/C][C]3.79103[/C][C]0.208971[/C][/ROW]
[ROW][C]184[/C][C]11[/C][C]11.9566[/C][C]-0.956644[/C][/ROW]
[ROW][C]185[/C][C]10[/C][C]12.3095[/C][C]-2.30953[/C][/ROW]
[ROW][C]186[/C][C]7[/C][C]5.79791[/C][C]1.20209[/C][/ROW]
[ROW][C]187[/C][C]12[/C][C]11.8835[/C][C]0.116476[/C][/ROW]
[ROW][C]188[/C][C]11[/C][C]12.9788[/C][C]-1.97878[/C][/ROW]
[ROW][C]189[/C][C]9[/C][C]9.95191[/C][C]-0.951911[/C][/ROW]
[ROW][C]190[/C][C]10[/C][C]12.5448[/C][C]-2.54483[/C][/ROW]
[ROW][C]191[/C][C]8[/C][C]10.6911[/C][C]-2.69107[/C][/ROW]
[ROW][C]192[/C][C]8[/C][C]8.03183[/C][C]-0.031829[/C][/ROW]
[ROW][C]193[/C][C]11[/C][C]10.4133[/C][C]0.586692[/C][/ROW]
[ROW][C]194[/C][C]12[/C][C]13.2041[/C][C]-1.20406[/C][/ROW]
[ROW][C]195[/C][C]10[/C][C]10.5718[/C][C]-0.571797[/C][/ROW]
[ROW][C]196[/C][C]10[/C][C]8.49802[/C][C]1.50198[/C][/ROW]
[ROW][C]197[/C][C]12[/C][C]14.4925[/C][C]-2.49251[/C][/ROW]
[ROW][C]198[/C][C]8[/C][C]7.40416[/C][C]0.595837[/C][/ROW]
[ROW][C]199[/C][C]11[/C][C]13.7055[/C][C]-2.70547[/C][/ROW]
[ROW][C]200[/C][C]8[/C][C]9.59022[/C][C]-1.59022[/C][/ROW]
[ROW][C]201[/C][C]10[/C][C]6.2386[/C][C]3.7614[/C][/ROW]
[ROW][C]202[/C][C]14[/C][C]16.8843[/C][C]-2.88432[/C][/ROW]
[ROW][C]203[/C][C]9[/C][C]11.0737[/C][C]-2.0737[/C][/ROW]
[ROW][C]204[/C][C]9[/C][C]9.37928[/C][C]-0.379278[/C][/ROW]
[ROW][C]205[/C][C]10[/C][C]7.30932[/C][C]2.69068[/C][/ROW]
[ROW][C]206[/C][C]13[/C][C]11.3579[/C][C]1.64211[/C][/ROW]
[ROW][C]207[/C][C]12[/C][C]9.81176[/C][C]2.18824[/C][/ROW]
[ROW][C]208[/C][C]13[/C][C]15.1409[/C][C]-2.14092[/C][/ROW]
[ROW][C]209[/C][C]8[/C][C]15.3542[/C][C]-7.35423[/C][/ROW]
[ROW][C]210[/C][C]3[/C][C]5.37105[/C][C]-2.37105[/C][/ROW]
[ROW][C]211[/C][C]8[/C][C]6.77423[/C][C]1.22577[/C][/ROW]
[ROW][C]212[/C][C]12[/C][C]11.8616[/C][C]0.138382[/C][/ROW]
[ROW][C]213[/C][C]11[/C][C]12.9601[/C][C]-1.96009[/C][/ROW]
[ROW][C]214[/C][C]9[/C][C]7.61024[/C][C]1.38976[/C][/ROW]
[ROW][C]215[/C][C]12[/C][C]10.7758[/C][C]1.22425[/C][/ROW]
[ROW][C]216[/C][C]12[/C][C]10.6469[/C][C]1.35309[/C][/ROW]
[ROW][C]217[/C][C]12[/C][C]12.1371[/C][C]-0.137128[/C][/ROW]
[ROW][C]218[/C][C]10[/C][C]8.08811[/C][C]1.91189[/C][/ROW]
[ROW][C]219[/C][C]13[/C][C]14.2275[/C][C]-1.2275[/C][/ROW]
[ROW][C]220[/C][C]9[/C][C]7.86286[/C][C]1.13714[/C][/ROW]
[ROW][C]221[/C][C]12[/C][C]11.7812[/C][C]0.218765[/C][/ROW]
[ROW][C]222[/C][C]11[/C][C]7.33494[/C][C]3.66506[/C][/ROW]
[ROW][C]223[/C][C]14[/C][C]14.0434[/C][C]-0.0433819[/C][/ROW]
[ROW][C]224[/C][C]11[/C][C]12.1738[/C][C]-1.17378[/C][/ROW]
[ROW][C]225[/C][C]9[/C][C]7.56556[/C][C]1.43444[/C][/ROW]
[ROW][C]226[/C][C]12[/C][C]13.6841[/C][C]-1.68409[/C][/ROW]
[ROW][C]227[/C][C]8[/C][C]4.30623[/C][C]3.69377[/C][/ROW]
[ROW][C]228[/C][C]15[/C][C]14.0944[/C][C]0.905593[/C][/ROW]
[ROW][C]229[/C][C]12[/C][C]9.0991[/C][C]2.9009[/C][/ROW]
[ROW][C]230[/C][C]14[/C][C]12.7417[/C][C]1.25831[/C][/ROW]
[ROW][C]231[/C][C]12[/C][C]14.369[/C][C]-2.36901[/C][/ROW]
[ROW][C]232[/C][C]9[/C][C]10.8681[/C][C]-1.8681[/C][/ROW]
[ROW][C]233[/C][C]9[/C][C]7.09767[/C][C]1.90233[/C][/ROW]
[ROW][C]234[/C][C]13[/C][C]10.5387[/C][C]2.46134[/C][/ROW]
[ROW][C]235[/C][C]13[/C][C]8.89215[/C][C]4.10785[/C][/ROW]
[ROW][C]236[/C][C]15[/C][C]15.0713[/C][C]-0.0712929[/C][/ROW]
[ROW][C]237[/C][C]11[/C][C]14.4829[/C][C]-3.4829[/C][/ROW]
[ROW][C]238[/C][C]7[/C][C]7.62323[/C][C]-0.623225[/C][/ROW]
[ROW][C]239[/C][C]10[/C][C]9.97728[/C][C]0.0227188[/C][/ROW]
[ROW][C]240[/C][C]11[/C][C]8.27395[/C][C]2.72605[/C][/ROW]
[ROW][C]241[/C][C]14[/C][C]11.6383[/C][C]2.36166[/C][/ROW]
[ROW][C]242[/C][C]14[/C][C]11.1735[/C][C]2.82647[/C][/ROW]
[ROW][C]243[/C][C]13[/C][C]12.166[/C][C]0.833999[/C][/ROW]
[ROW][C]244[/C][C]12[/C][C]13.9604[/C][C]-1.96043[/C][/ROW]
[ROW][C]245[/C][C]8[/C][C]5.59634[/C][C]2.40366[/C][/ROW]
[ROW][C]246[/C][C]13[/C][C]14.7124[/C][C]-1.71245[/C][/ROW]
[ROW][C]247[/C][C]9[/C][C]7.76644[/C][C]1.23356[/C][/ROW]
[ROW][C]248[/C][C]12[/C][C]8.73984[/C][C]3.26016[/C][/ROW]
[ROW][C]249[/C][C]13[/C][C]13.2408[/C][C]-0.240794[/C][/ROW]
[ROW][C]250[/C][C]11[/C][C]11.2209[/C][C]-0.220947[/C][/ROW]
[ROW][C]251[/C][C]11[/C][C]8.72654[/C][C]2.27346[/C][/ROW]
[ROW][C]252[/C][C]13[/C][C]11.626[/C][C]1.37403[/C][/ROW]
[ROW][C]253[/C][C]12[/C][C]10.5022[/C][C]1.49782[/C][/ROW]
[ROW][C]254[/C][C]12[/C][C]10.4667[/C][C]1.53329[/C][/ROW]
[ROW][C]255[/C][C]10[/C][C]10.4101[/C][C]-0.41007[/C][/ROW]
[ROW][C]256[/C][C]9[/C][C]10.2077[/C][C]-1.2077[/C][/ROW]
[ROW][C]257[/C][C]10[/C][C]7.74665[/C][C]2.25335[/C][/ROW]
[ROW][C]258[/C][C]13[/C][C]10.7368[/C][C]2.26325[/C][/ROW]
[ROW][C]259[/C][C]13[/C][C]14.3012[/C][C]-1.30118[/C][/ROW]
[ROW][C]260[/C][C]9[/C][C]8.63329[/C][C]0.366705[/C][/ROW]
[ROW][C]261[/C][C]11[/C][C]9.57871[/C][C]1.42129[/C][/ROW]
[ROW][C]262[/C][C]12[/C][C]14.687[/C][C]-2.68702[/C][/ROW]
[ROW][C]263[/C][C]8[/C][C]5.91168[/C][C]2.08832[/C][/ROW]
[ROW][C]264[/C][C]12[/C][C]10.909[/C][C]1.09103[/C][/ROW]
[ROW][C]265[/C][C]12[/C][C]10.881[/C][C]1.11904[/C][/ROW]
[ROW][C]266[/C][C]12[/C][C]13.8961[/C][C]-1.89607[/C][/ROW]
[ROW][C]267[/C][C]9[/C][C]7.61119[/C][C]1.38881[/C][/ROW]
[ROW][C]268[/C][C]12[/C][C]11.5309[/C][C]0.469098[/C][/ROW]
[ROW][C]269[/C][C]12[/C][C]12.4978[/C][C]-0.497821[/C][/ROW]
[ROW][C]270[/C][C]11[/C][C]10.0931[/C][C]0.90691[/C][/ROW]
[ROW][C]271[/C][C]12[/C][C]16.9389[/C][C]-4.93893[/C][/ROW]
[ROW][C]272[/C][C]6[/C][C]9.33133[/C][C]-3.33133[/C][/ROW]
[ROW][C]273[/C][C]7[/C][C]7.80067[/C][C]-0.800672[/C][/ROW]
[ROW][C]274[/C][C]10[/C][C]9.07141[/C][C]0.928588[/C][/ROW]
[ROW][C]275[/C][C]12[/C][C]13.2741[/C][C]-1.27408[/C][/ROW]
[ROW][C]276[/C][C]10[/C][C]8.77411[/C][C]1.22589[/C][/ROW]
[ROW][C]277[/C][C]12[/C][C]13.6281[/C][C]-1.62808[/C][/ROW]
[ROW][C]278[/C][C]9[/C][C]15.6387[/C][C]-6.63869[/C][/ROW]
[ROW][C]279[/C][C]3[/C][C]NA[/C][C]NA[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263726&T=4

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263726&T=4

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Multiple Linear Regression - Actuals, Interpolation, and Residuals
Time or IndexActualsInterpolationForecastResidualsPrediction Error
11210.17531.82468
2811.211-3.211
31110.4710.529002
41311.34671.65329
51110.78450.215495
61010.4808-0.480822
7710.32-3.31998
81010.3281-0.328116
91511.73723.26284
101212.2875-0.287495
111210.54541.45459
121011.6711-1.6711
131010.1285-0.128458
141410.90093.09905
15611.2559-5.25585
161210.54381.45616
171410.43513.56487
181110.88610.113918
19811.016-3.01599
201211.2030.797011
211511.24743.75262
221310.94832.05169
231110.87560.124445
241210.90011.09987
25710.8842-3.88418
261110.75950.240529
27710.802-3.80205
281210.48831.5117
291211.35560.644442
301310.57032.42965
3199.3918-0.3918
321110.4840.516003
331210.66791.33211
341510.24134.75869
351210.30951.69046
36610.9319-4.93186
37510.8019-5.80192
381310.6982.302
391111.2596-0.259603
40610.2962-4.2962
411210.6591.341
421010.8875-0.887478
43610.701-4.70095
44129.736352.26365
45119.627931.37207
46611.5499-5.54987
471210.69281.30723
481211.13850.861517
49811.2237-3.22375
501010.719-0.718953
511110.74150.258529
52710.4918-3.49184
531210.62141.37864
541311.31611.68386
551411.4172.58304
561210.93791.06209
5769.76446-3.76446
581410.30933.69069
591010.5958-0.595815
601210.77221.22778
611111.3098-0.309796
621010.828-0.827961
6379.12845-2.12845
641210.5441.45601
65710.5823-3.58233
661210.18391.81613
671210.9381.06199
681011.2951-1.29507
691010.5108-0.510837
701210.22551.77454
711210.62611.37394
721210.86441.13557
73810.7176-2.7176
741011.8362-1.83624
7559.77696-4.77696
761010.1211-0.121129
77108.35441.6456
781212.5037-0.503721
791111.9417-0.941739
8097.704131.29587
811211.70130.298658
821111.7729-0.772893
83108.510781.48922
841212.7935-0.793483
851011.0238-1.02383
8698.946040.053964
871110.2130.787028
881215.9657-3.96567
8976.701870.298131
90119.72541.2746
911216.6588-4.65876
9266.43893-0.438927
9395.391153.60885
941514.12630.873728
95109.747320.252682
961110.35830.641747
971210.80011.1999
981210.60571.3943
991211.46580.53417
1001113.1154-2.11543
10198.939320.0606825
1021110.16040.839627
103129.480562.51944
104129.054032.94597
1051416.834-2.83396
10688.63209-0.632094
1071011.7377-1.73771
10899.48129-0.481286
1091012.0971-2.09712
110910.1462-1.14618
111109.257290.742709
1121212.2583-0.258303
1131113.1163-2.11631
11497.51991.4801
115119.260931.73907
1161210.89881.10119
1171216.1737-4.1737
11875.259441.74056
1191211.14970.850313
1201211.32070.679341
1211212.8912-0.891233
122105.892314.10769
1231515.897-0.897045
124106.238183.76182
1251515.9047-0.904705
126105.847114.15289
1271516.0107-1.01069
12894.986224.01378
1291514.660.340036
130129.672512.32749
1311311.30911.6909
1321210.94061.05943
1331214.5846-2.58461
134810.2481-2.24814
13594.139784.86022
1361514.7070.292986
1371210.74161.25841
138127.756684.24332
1391514.89520.104758
1401110.45320.546843
1411214.7518-2.75177
14262.532593.46741
1431413.10610.893879
1441210.40631.59375
1451210.95541.04461
1461211.72120.278768
1471111.2804-0.280363
1481211.06070.939264
1491211.00380.99624
1501210.65231.34773
1511214.622-2.62201
152811.1756-3.17564
15387.191880.808122
1541210.05181.94819
1551212.6428-0.642793
1561112.6529-1.65289
1571010.9476-0.947582
158119.772041.22796
1591210.63251.36751
1601311.29591.70411
1611210.55491.44515
1621213.0581-1.05806
1631010.7306-0.730593
1641010.5201-0.520081
1651114.0356-3.03557
16685.613632.38637
1671213.5088-1.50875
16897.851351.14865
1691214.6779-2.67792
17098.627120.372881
171117.878133.12187
1721517.49-2.48997
173810.7941-2.79414
17487.992150.00785145
1751110.92770.0723353
1761110.51640.483573
177118.659612.34039
1781315.7871-2.78711
17975.740961.25904
1801214.0395-2.03945
181810.6202-2.62018
182814.4421-6.44207
18343.791030.208971
1841111.9566-0.956644
1851012.3095-2.30953
18675.797911.20209
1871211.88350.116476
1881112.9788-1.97878
18999.95191-0.951911
1901012.5448-2.54483
191810.6911-2.69107
19288.03183-0.031829
1931110.41330.586692
1941213.2041-1.20406
1951010.5718-0.571797
196108.498021.50198
1971214.4925-2.49251
19887.404160.595837
1991113.7055-2.70547
20089.59022-1.59022
201106.23863.7614
2021416.8843-2.88432
203911.0737-2.0737
20499.37928-0.379278
205107.309322.69068
2061311.35791.64211
207129.811762.18824
2081315.1409-2.14092
209815.3542-7.35423
21035.37105-2.37105
21186.774231.22577
2121211.86160.138382
2131112.9601-1.96009
21497.610241.38976
2151210.77581.22425
2161210.64691.35309
2171212.1371-0.137128
218108.088111.91189
2191314.2275-1.2275
22097.862861.13714
2211211.78120.218765
222117.334943.66506
2231414.0434-0.0433819
2241112.1738-1.17378
22597.565561.43444
2261213.6841-1.68409
22784.306233.69377
2281514.09440.905593
229129.09912.9009
2301412.74171.25831
2311214.369-2.36901
232910.8681-1.8681
23397.097671.90233
2341310.53872.46134
235138.892154.10785
2361515.0713-0.0712929
2371114.4829-3.4829
23877.62323-0.623225
239109.977280.0227188
240118.273952.72605
2411411.63832.36166
2421411.17352.82647
2431312.1660.833999
2441213.9604-1.96043
24585.596342.40366
2461314.7124-1.71245
24797.766441.23356
248128.739843.26016
2491313.2408-0.240794
2501111.2209-0.220947
251118.726542.27346
2521311.6261.37403
2531210.50221.49782
2541210.46671.53329
2551010.4101-0.41007
256910.2077-1.2077
257107.746652.25335
2581310.73682.26325
2591314.3012-1.30118
26098.633290.366705
261119.578711.42129
2621214.687-2.68702
26385.911682.08832
2641210.9091.09103
2651210.8811.11904
2661213.8961-1.89607
26797.611191.38881
2681211.53090.469098
2691212.4978-0.497821
2701110.09310.90691
2711216.9389-4.93893
27269.33133-3.33133
27377.80067-0.800672
274109.071410.928588
2751213.2741-1.27408
276108.774111.22589
2771213.6281-1.62808
278915.6387-6.63869
2793NANA






Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.5396020.9207960.460398
90.8020370.3959260.197963
100.6997430.6005140.300257
110.6113210.7773580.388679
120.6359870.7280260.364013
130.5334840.9330310.466516
140.5375520.9248960.462448
150.8407440.3185110.159256
160.8432120.3135760.156788
170.8588110.2823780.141189
180.8097240.3805530.190276
190.8191280.3617430.180872
200.7725090.4549820.227491
210.8558340.2883320.144166
220.8382060.3235870.161794
230.7951850.4096290.204815
240.7464970.5070070.253503
250.7996320.4007350.200368
260.7558880.4882240.244112
270.8334140.3331710.166586
280.8337020.3325970.166298
290.7957990.4084020.204201
300.7697630.4604740.230237
310.7364370.5271250.263563
320.7140810.5718370.285919
330.6788740.6422520.321126
340.7661540.4676910.233846
350.7369150.5261710.263085
360.8715240.2569530.128476
370.969890.06021950.0301097
380.9706730.05865330.0293266
390.9615020.07699640.0384982
400.9828890.03422190.0171109
410.9785550.04288930.0214446
420.9723190.05536210.027681
430.9858680.02826450.0141323
440.9840280.03194390.0159719
450.9797510.04049840.0202492
460.9915960.01680780.00840388
470.9898650.0202710.0101355
480.9869050.02618970.0130948
490.9871410.02571780.0128589
500.9830820.0338360.016918
510.9782040.04359260.0217963
520.9876630.02467320.0123366
530.9853580.02928460.0146423
540.9850560.02988710.0149435
550.9880380.02392430.0119622
560.9852120.02957670.0147884
570.9913560.01728860.00864429
580.9939760.01204720.00602361
590.9920610.01587890.00793943
600.9901820.01963610.00981804
610.9871940.02561230.0128061
620.9839220.03215570.0160778
630.9830770.03384650.0169232
640.9794430.04111340.0205567
650.9838180.0323640.016182
660.9827060.03458810.0172941
670.9794560.0410880.020544
680.9759970.04800660.0240033
690.9706410.05871780.0293589
700.9667360.06652810.033264
710.9616520.0766960.038348
720.9547910.09041870.0452094
730.9556170.08876620.0443831
740.9522550.09549040.0477452
750.978420.043160.02158
760.9730140.05397230.0269862
770.969360.06127950.0306398
780.9625120.0749750.0374875
790.9555990.08880210.0444011
800.9504350.099130.049565
810.9402290.1195430.0597713
820.9297070.1405870.0702935
830.9222680.1554640.0777321
840.90920.18160.0908001
850.8962060.2075890.103794
860.878540.242920.12146
870.8615550.2768890.138445
880.8958240.2083520.104176
890.8793620.2412760.120638
900.8660660.2678680.133934
910.9186330.1627340.0813672
920.904650.1907010.0953503
930.9286120.1427760.0713879
940.9179870.1640250.0820127
950.9037120.1925760.0962879
960.8895210.2209580.110479
970.8778340.2443320.122166
980.866570.266860.13343
990.8470460.3059070.152954
1000.8431540.3136920.156846
1010.8208730.3582540.179127
1020.8009610.3980780.199039
1030.8046190.3907610.195381
1040.8217270.3565460.178273
1050.8350790.3298420.164921
1060.814080.371840.18592
1070.8031750.393650.196825
1080.779510.440980.22049
1090.7770690.4458610.222931
1100.7579520.4840950.242048
1110.7329780.5340430.267022
1120.704150.5916990.29585
1130.7049860.5900270.295014
1140.6851170.6297670.314883
1150.6720670.6558670.327933
1160.6465680.7068630.353432
1170.7250630.5498750.274937
1180.7137180.5725650.286282
1190.6875950.624810.312405
1200.6589540.6820930.341046
1210.6320280.7359440.367972
1220.7020130.5959730.297987
1230.6767230.6465540.323277
1240.7264130.5471750.273587
1250.703160.593680.29684
1260.7662620.4674770.233738
1270.7463980.5072050.253602
1280.7988130.4023740.201187
1290.7740040.4519930.225996
1300.7737310.4525380.226269
1310.7609990.4780030.239001
1320.73830.5233990.2617
1330.75140.4972010.2486
1340.7542920.4914150.245708
1350.84160.3168010.1584
1360.8203020.3593950.179698
1370.8046220.3907560.195378
1380.8584940.2830120.141506
1390.8385540.3228910.161446
1400.8173610.3652790.182639
1410.8264290.3471420.173571
1420.8564240.2871510.143576
1430.8382630.3234740.161737
1440.8285290.3429410.171471
1450.8110120.3779770.188988
1460.7881060.4237880.211894
1470.7643190.4713620.235681
1480.7415490.5169020.258451
1490.718860.562280.28114
1500.7002880.5994240.299712
1510.7167250.566550.283275
1520.7493780.5012440.250622
1530.7256150.548770.274385
1540.7331370.5337250.266863
1550.7079280.5841430.292072
1560.7001060.5997880.299894
1570.6783870.6432250.321613
1580.6570810.6858390.342919
1590.6336050.7327890.366395
1600.6263910.7472190.373609
1610.6161940.7676110.383806
1620.5914810.8170390.408519
1630.5633640.8732720.436636
1640.5312870.9374250.468713
1650.5581730.8836550.441827
1660.5622180.8755630.437782
1670.5430850.9138310.456915
1680.5183210.9633570.481679
1690.5474770.9050470.452523
1700.513580.9728390.48642
1710.5282050.943590.471795
1720.5345140.9309720.465486
1730.5561420.8877150.443858
1740.5208390.9583220.479161
1750.4851170.9702330.514883
1760.4546250.9092490.545375
1770.4591940.9183880.540806
1780.4624150.924830.537585
1790.4435250.887050.556475
1800.4374180.8748350.562582
1810.4520350.904070.547965
1820.6882490.6235020.311751
1830.6585120.6829760.341488
1840.6303170.7393670.369683
1850.6270350.745930.372965
1860.6005340.7989330.399466
1870.5643260.8713490.435674
1880.5634850.873030.436515
1890.5413480.9173050.458652
1900.5544090.8911830.445591
1910.5779010.8441990.422099
1920.5410170.9179670.458983
1930.5058920.9882160.494108
1940.4800540.9601070.519946
1950.4439280.8878570.556072
1960.4192730.8385460.580727
1970.4221960.8443920.577804
1980.3870810.7741610.612919
1990.4012050.802410.598795
2000.3898050.7796110.610195
2010.4613340.9226680.538666
2020.5150070.9699860.484993
2030.5235930.9528150.476407
2040.4846820.9693630.515318
2050.5008680.9982640.499132
2060.4872120.9744240.512788
2070.4707910.9415820.529209
2080.4732830.9465670.526717
2090.7938730.4122540.206127
2100.7974570.4050870.202543
2110.7713830.4572340.228617
2120.7387680.5224640.261232
2130.7469750.506050.253025
2140.7209120.5581770.279088
2150.6930840.6138320.306916
2160.6631270.6737470.336873
2170.6233560.7532890.376644
2180.608780.7824410.39122
2190.5873620.8252750.412638
2200.5512580.8974830.448742
2210.5080680.9838630.491932
2220.5716640.8566710.428336
2230.5316390.9367220.468361
2240.4983040.9966090.501696
2250.4732910.9465830.526709
2260.4413530.8827070.558647
2270.5041490.9917030.495851
2280.4644440.9288880.535556
2290.5081380.9837230.491862
2300.4859130.9718260.514087
2310.4788340.9576670.521166
2320.4571330.9142660.542867
2330.4417330.8834660.558267
2340.4463190.8926390.553681
2350.5292940.9414120.470706
2360.4905680.9811350.509432
2370.561440.877120.43856
2380.513590.972820.48641
2390.4895090.9790180.510491
2400.4970820.9941640.502918
2410.4979380.9958760.502062
2420.5825730.8348530.417427
2430.5326120.9347750.467388
2440.5190420.9619170.480958
2450.503490.993020.49651
2460.4552440.9104880.544756
2470.4085480.8170950.591452
2480.4681920.9363830.531808
2490.4088830.8177660.591117
2500.3514460.7028920.648554
2510.3793180.7586360.620682
2520.3608340.7216680.639166
2530.3496180.6992360.650382
2540.4905780.9811560.509422
2550.5449330.9101350.455067
2560.4930050.9860110.506995
2570.5187660.9624690.481234
2580.7453420.5093160.254658
2590.7203870.5592260.279613
2600.6572050.6855890.342795
2610.5805810.8388380.419419
2620.501760.996480.49824
2630.6507350.698530.349265
2640.6506240.6987520.349376
2650.6130160.7739690.386984
2660.6025080.7949840.397492
2670.4943750.9887490.505625
2680.4382420.8764840.561758
2690.3360270.6720550.663973
2700.6965740.6068520.303426
2710.9187790.1624410.0812206

\begin{tabular}{lllllllll}
\hline
Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
p-values & Alternative Hypothesis \tabularnewline
breakpoint index & greater & 2-sided & less \tabularnewline
8 & 0.539602 & 0.920796 & 0.460398 \tabularnewline
9 & 0.802037 & 0.395926 & 0.197963 \tabularnewline
10 & 0.699743 & 0.600514 & 0.300257 \tabularnewline
11 & 0.611321 & 0.777358 & 0.388679 \tabularnewline
12 & 0.635987 & 0.728026 & 0.364013 \tabularnewline
13 & 0.533484 & 0.933031 & 0.466516 \tabularnewline
14 & 0.537552 & 0.924896 & 0.462448 \tabularnewline
15 & 0.840744 & 0.318511 & 0.159256 \tabularnewline
16 & 0.843212 & 0.313576 & 0.156788 \tabularnewline
17 & 0.858811 & 0.282378 & 0.141189 \tabularnewline
18 & 0.809724 & 0.380553 & 0.190276 \tabularnewline
19 & 0.819128 & 0.361743 & 0.180872 \tabularnewline
20 & 0.772509 & 0.454982 & 0.227491 \tabularnewline
21 & 0.855834 & 0.288332 & 0.144166 \tabularnewline
22 & 0.838206 & 0.323587 & 0.161794 \tabularnewline
23 & 0.795185 & 0.409629 & 0.204815 \tabularnewline
24 & 0.746497 & 0.507007 & 0.253503 \tabularnewline
25 & 0.799632 & 0.400735 & 0.200368 \tabularnewline
26 & 0.755888 & 0.488224 & 0.244112 \tabularnewline
27 & 0.833414 & 0.333171 & 0.166586 \tabularnewline
28 & 0.833702 & 0.332597 & 0.166298 \tabularnewline
29 & 0.795799 & 0.408402 & 0.204201 \tabularnewline
30 & 0.769763 & 0.460474 & 0.230237 \tabularnewline
31 & 0.736437 & 0.527125 & 0.263563 \tabularnewline
32 & 0.714081 & 0.571837 & 0.285919 \tabularnewline
33 & 0.678874 & 0.642252 & 0.321126 \tabularnewline
34 & 0.766154 & 0.467691 & 0.233846 \tabularnewline
35 & 0.736915 & 0.526171 & 0.263085 \tabularnewline
36 & 0.871524 & 0.256953 & 0.128476 \tabularnewline
37 & 0.96989 & 0.0602195 & 0.0301097 \tabularnewline
38 & 0.970673 & 0.0586533 & 0.0293266 \tabularnewline
39 & 0.961502 & 0.0769964 & 0.0384982 \tabularnewline
40 & 0.982889 & 0.0342219 & 0.0171109 \tabularnewline
41 & 0.978555 & 0.0428893 & 0.0214446 \tabularnewline
42 & 0.972319 & 0.0553621 & 0.027681 \tabularnewline
43 & 0.985868 & 0.0282645 & 0.0141323 \tabularnewline
44 & 0.984028 & 0.0319439 & 0.0159719 \tabularnewline
45 & 0.979751 & 0.0404984 & 0.0202492 \tabularnewline
46 & 0.991596 & 0.0168078 & 0.00840388 \tabularnewline
47 & 0.989865 & 0.020271 & 0.0101355 \tabularnewline
48 & 0.986905 & 0.0261897 & 0.0130948 \tabularnewline
49 & 0.987141 & 0.0257178 & 0.0128589 \tabularnewline
50 & 0.983082 & 0.033836 & 0.016918 \tabularnewline
51 & 0.978204 & 0.0435926 & 0.0217963 \tabularnewline
52 & 0.987663 & 0.0246732 & 0.0123366 \tabularnewline
53 & 0.985358 & 0.0292846 & 0.0146423 \tabularnewline
54 & 0.985056 & 0.0298871 & 0.0149435 \tabularnewline
55 & 0.988038 & 0.0239243 & 0.0119622 \tabularnewline
56 & 0.985212 & 0.0295767 & 0.0147884 \tabularnewline
57 & 0.991356 & 0.0172886 & 0.00864429 \tabularnewline
58 & 0.993976 & 0.0120472 & 0.00602361 \tabularnewline
59 & 0.992061 & 0.0158789 & 0.00793943 \tabularnewline
60 & 0.990182 & 0.0196361 & 0.00981804 \tabularnewline
61 & 0.987194 & 0.0256123 & 0.0128061 \tabularnewline
62 & 0.983922 & 0.0321557 & 0.0160778 \tabularnewline
63 & 0.983077 & 0.0338465 & 0.0169232 \tabularnewline
64 & 0.979443 & 0.0411134 & 0.0205567 \tabularnewline
65 & 0.983818 & 0.032364 & 0.016182 \tabularnewline
66 & 0.982706 & 0.0345881 & 0.0172941 \tabularnewline
67 & 0.979456 & 0.041088 & 0.020544 \tabularnewline
68 & 0.975997 & 0.0480066 & 0.0240033 \tabularnewline
69 & 0.970641 & 0.0587178 & 0.0293589 \tabularnewline
70 & 0.966736 & 0.0665281 & 0.033264 \tabularnewline
71 & 0.961652 & 0.076696 & 0.038348 \tabularnewline
72 & 0.954791 & 0.0904187 & 0.0452094 \tabularnewline
73 & 0.955617 & 0.0887662 & 0.0443831 \tabularnewline
74 & 0.952255 & 0.0954904 & 0.0477452 \tabularnewline
75 & 0.97842 & 0.04316 & 0.02158 \tabularnewline
76 & 0.973014 & 0.0539723 & 0.0269862 \tabularnewline
77 & 0.96936 & 0.0612795 & 0.0306398 \tabularnewline
78 & 0.962512 & 0.074975 & 0.0374875 \tabularnewline
79 & 0.955599 & 0.0888021 & 0.0444011 \tabularnewline
80 & 0.950435 & 0.09913 & 0.049565 \tabularnewline
81 & 0.940229 & 0.119543 & 0.0597713 \tabularnewline
82 & 0.929707 & 0.140587 & 0.0702935 \tabularnewline
83 & 0.922268 & 0.155464 & 0.0777321 \tabularnewline
84 & 0.9092 & 0.1816 & 0.0908001 \tabularnewline
85 & 0.896206 & 0.207589 & 0.103794 \tabularnewline
86 & 0.87854 & 0.24292 & 0.12146 \tabularnewline
87 & 0.861555 & 0.276889 & 0.138445 \tabularnewline
88 & 0.895824 & 0.208352 & 0.104176 \tabularnewline
89 & 0.879362 & 0.241276 & 0.120638 \tabularnewline
90 & 0.866066 & 0.267868 & 0.133934 \tabularnewline
91 & 0.918633 & 0.162734 & 0.0813672 \tabularnewline
92 & 0.90465 & 0.190701 & 0.0953503 \tabularnewline
93 & 0.928612 & 0.142776 & 0.0713879 \tabularnewline
94 & 0.917987 & 0.164025 & 0.0820127 \tabularnewline
95 & 0.903712 & 0.192576 & 0.0962879 \tabularnewline
96 & 0.889521 & 0.220958 & 0.110479 \tabularnewline
97 & 0.877834 & 0.244332 & 0.122166 \tabularnewline
98 & 0.86657 & 0.26686 & 0.13343 \tabularnewline
99 & 0.847046 & 0.305907 & 0.152954 \tabularnewline
100 & 0.843154 & 0.313692 & 0.156846 \tabularnewline
101 & 0.820873 & 0.358254 & 0.179127 \tabularnewline
102 & 0.800961 & 0.398078 & 0.199039 \tabularnewline
103 & 0.804619 & 0.390761 & 0.195381 \tabularnewline
104 & 0.821727 & 0.356546 & 0.178273 \tabularnewline
105 & 0.835079 & 0.329842 & 0.164921 \tabularnewline
106 & 0.81408 & 0.37184 & 0.18592 \tabularnewline
107 & 0.803175 & 0.39365 & 0.196825 \tabularnewline
108 & 0.77951 & 0.44098 & 0.22049 \tabularnewline
109 & 0.777069 & 0.445861 & 0.222931 \tabularnewline
110 & 0.757952 & 0.484095 & 0.242048 \tabularnewline
111 & 0.732978 & 0.534043 & 0.267022 \tabularnewline
112 & 0.70415 & 0.591699 & 0.29585 \tabularnewline
113 & 0.704986 & 0.590027 & 0.295014 \tabularnewline
114 & 0.685117 & 0.629767 & 0.314883 \tabularnewline
115 & 0.672067 & 0.655867 & 0.327933 \tabularnewline
116 & 0.646568 & 0.706863 & 0.353432 \tabularnewline
117 & 0.725063 & 0.549875 & 0.274937 \tabularnewline
118 & 0.713718 & 0.572565 & 0.286282 \tabularnewline
119 & 0.687595 & 0.62481 & 0.312405 \tabularnewline
120 & 0.658954 & 0.682093 & 0.341046 \tabularnewline
121 & 0.632028 & 0.735944 & 0.367972 \tabularnewline
122 & 0.702013 & 0.595973 & 0.297987 \tabularnewline
123 & 0.676723 & 0.646554 & 0.323277 \tabularnewline
124 & 0.726413 & 0.547175 & 0.273587 \tabularnewline
125 & 0.70316 & 0.59368 & 0.29684 \tabularnewline
126 & 0.766262 & 0.467477 & 0.233738 \tabularnewline
127 & 0.746398 & 0.507205 & 0.253602 \tabularnewline
128 & 0.798813 & 0.402374 & 0.201187 \tabularnewline
129 & 0.774004 & 0.451993 & 0.225996 \tabularnewline
130 & 0.773731 & 0.452538 & 0.226269 \tabularnewline
131 & 0.760999 & 0.478003 & 0.239001 \tabularnewline
132 & 0.7383 & 0.523399 & 0.2617 \tabularnewline
133 & 0.7514 & 0.497201 & 0.2486 \tabularnewline
134 & 0.754292 & 0.491415 & 0.245708 \tabularnewline
135 & 0.8416 & 0.316801 & 0.1584 \tabularnewline
136 & 0.820302 & 0.359395 & 0.179698 \tabularnewline
137 & 0.804622 & 0.390756 & 0.195378 \tabularnewline
138 & 0.858494 & 0.283012 & 0.141506 \tabularnewline
139 & 0.838554 & 0.322891 & 0.161446 \tabularnewline
140 & 0.817361 & 0.365279 & 0.182639 \tabularnewline
141 & 0.826429 & 0.347142 & 0.173571 \tabularnewline
142 & 0.856424 & 0.287151 & 0.143576 \tabularnewline
143 & 0.838263 & 0.323474 & 0.161737 \tabularnewline
144 & 0.828529 & 0.342941 & 0.171471 \tabularnewline
145 & 0.811012 & 0.377977 & 0.188988 \tabularnewline
146 & 0.788106 & 0.423788 & 0.211894 \tabularnewline
147 & 0.764319 & 0.471362 & 0.235681 \tabularnewline
148 & 0.741549 & 0.516902 & 0.258451 \tabularnewline
149 & 0.71886 & 0.56228 & 0.28114 \tabularnewline
150 & 0.700288 & 0.599424 & 0.299712 \tabularnewline
151 & 0.716725 & 0.56655 & 0.283275 \tabularnewline
152 & 0.749378 & 0.501244 & 0.250622 \tabularnewline
153 & 0.725615 & 0.54877 & 0.274385 \tabularnewline
154 & 0.733137 & 0.533725 & 0.266863 \tabularnewline
155 & 0.707928 & 0.584143 & 0.292072 \tabularnewline
156 & 0.700106 & 0.599788 & 0.299894 \tabularnewline
157 & 0.678387 & 0.643225 & 0.321613 \tabularnewline
158 & 0.657081 & 0.685839 & 0.342919 \tabularnewline
159 & 0.633605 & 0.732789 & 0.366395 \tabularnewline
160 & 0.626391 & 0.747219 & 0.373609 \tabularnewline
161 & 0.616194 & 0.767611 & 0.383806 \tabularnewline
162 & 0.591481 & 0.817039 & 0.408519 \tabularnewline
163 & 0.563364 & 0.873272 & 0.436636 \tabularnewline
164 & 0.531287 & 0.937425 & 0.468713 \tabularnewline
165 & 0.558173 & 0.883655 & 0.441827 \tabularnewline
166 & 0.562218 & 0.875563 & 0.437782 \tabularnewline
167 & 0.543085 & 0.913831 & 0.456915 \tabularnewline
168 & 0.518321 & 0.963357 & 0.481679 \tabularnewline
169 & 0.547477 & 0.905047 & 0.452523 \tabularnewline
170 & 0.51358 & 0.972839 & 0.48642 \tabularnewline
171 & 0.528205 & 0.94359 & 0.471795 \tabularnewline
172 & 0.534514 & 0.930972 & 0.465486 \tabularnewline
173 & 0.556142 & 0.887715 & 0.443858 \tabularnewline
174 & 0.520839 & 0.958322 & 0.479161 \tabularnewline
175 & 0.485117 & 0.970233 & 0.514883 \tabularnewline
176 & 0.454625 & 0.909249 & 0.545375 \tabularnewline
177 & 0.459194 & 0.918388 & 0.540806 \tabularnewline
178 & 0.462415 & 0.92483 & 0.537585 \tabularnewline
179 & 0.443525 & 0.88705 & 0.556475 \tabularnewline
180 & 0.437418 & 0.874835 & 0.562582 \tabularnewline
181 & 0.452035 & 0.90407 & 0.547965 \tabularnewline
182 & 0.688249 & 0.623502 & 0.311751 \tabularnewline
183 & 0.658512 & 0.682976 & 0.341488 \tabularnewline
184 & 0.630317 & 0.739367 & 0.369683 \tabularnewline
185 & 0.627035 & 0.74593 & 0.372965 \tabularnewline
186 & 0.600534 & 0.798933 & 0.399466 \tabularnewline
187 & 0.564326 & 0.871349 & 0.435674 \tabularnewline
188 & 0.563485 & 0.87303 & 0.436515 \tabularnewline
189 & 0.541348 & 0.917305 & 0.458652 \tabularnewline
190 & 0.554409 & 0.891183 & 0.445591 \tabularnewline
191 & 0.577901 & 0.844199 & 0.422099 \tabularnewline
192 & 0.541017 & 0.917967 & 0.458983 \tabularnewline
193 & 0.505892 & 0.988216 & 0.494108 \tabularnewline
194 & 0.480054 & 0.960107 & 0.519946 \tabularnewline
195 & 0.443928 & 0.887857 & 0.556072 \tabularnewline
196 & 0.419273 & 0.838546 & 0.580727 \tabularnewline
197 & 0.422196 & 0.844392 & 0.577804 \tabularnewline
198 & 0.387081 & 0.774161 & 0.612919 \tabularnewline
199 & 0.401205 & 0.80241 & 0.598795 \tabularnewline
200 & 0.389805 & 0.779611 & 0.610195 \tabularnewline
201 & 0.461334 & 0.922668 & 0.538666 \tabularnewline
202 & 0.515007 & 0.969986 & 0.484993 \tabularnewline
203 & 0.523593 & 0.952815 & 0.476407 \tabularnewline
204 & 0.484682 & 0.969363 & 0.515318 \tabularnewline
205 & 0.500868 & 0.998264 & 0.499132 \tabularnewline
206 & 0.487212 & 0.974424 & 0.512788 \tabularnewline
207 & 0.470791 & 0.941582 & 0.529209 \tabularnewline
208 & 0.473283 & 0.946567 & 0.526717 \tabularnewline
209 & 0.793873 & 0.412254 & 0.206127 \tabularnewline
210 & 0.797457 & 0.405087 & 0.202543 \tabularnewline
211 & 0.771383 & 0.457234 & 0.228617 \tabularnewline
212 & 0.738768 & 0.522464 & 0.261232 \tabularnewline
213 & 0.746975 & 0.50605 & 0.253025 \tabularnewline
214 & 0.720912 & 0.558177 & 0.279088 \tabularnewline
215 & 0.693084 & 0.613832 & 0.306916 \tabularnewline
216 & 0.663127 & 0.673747 & 0.336873 \tabularnewline
217 & 0.623356 & 0.753289 & 0.376644 \tabularnewline
218 & 0.60878 & 0.782441 & 0.39122 \tabularnewline
219 & 0.587362 & 0.825275 & 0.412638 \tabularnewline
220 & 0.551258 & 0.897483 & 0.448742 \tabularnewline
221 & 0.508068 & 0.983863 & 0.491932 \tabularnewline
222 & 0.571664 & 0.856671 & 0.428336 \tabularnewline
223 & 0.531639 & 0.936722 & 0.468361 \tabularnewline
224 & 0.498304 & 0.996609 & 0.501696 \tabularnewline
225 & 0.473291 & 0.946583 & 0.526709 \tabularnewline
226 & 0.441353 & 0.882707 & 0.558647 \tabularnewline
227 & 0.504149 & 0.991703 & 0.495851 \tabularnewline
228 & 0.464444 & 0.928888 & 0.535556 \tabularnewline
229 & 0.508138 & 0.983723 & 0.491862 \tabularnewline
230 & 0.485913 & 0.971826 & 0.514087 \tabularnewline
231 & 0.478834 & 0.957667 & 0.521166 \tabularnewline
232 & 0.457133 & 0.914266 & 0.542867 \tabularnewline
233 & 0.441733 & 0.883466 & 0.558267 \tabularnewline
234 & 0.446319 & 0.892639 & 0.553681 \tabularnewline
235 & 0.529294 & 0.941412 & 0.470706 \tabularnewline
236 & 0.490568 & 0.981135 & 0.509432 \tabularnewline
237 & 0.56144 & 0.87712 & 0.43856 \tabularnewline
238 & 0.51359 & 0.97282 & 0.48641 \tabularnewline
239 & 0.489509 & 0.979018 & 0.510491 \tabularnewline
240 & 0.497082 & 0.994164 & 0.502918 \tabularnewline
241 & 0.497938 & 0.995876 & 0.502062 \tabularnewline
242 & 0.582573 & 0.834853 & 0.417427 \tabularnewline
243 & 0.532612 & 0.934775 & 0.467388 \tabularnewline
244 & 0.519042 & 0.961917 & 0.480958 \tabularnewline
245 & 0.50349 & 0.99302 & 0.49651 \tabularnewline
246 & 0.455244 & 0.910488 & 0.544756 \tabularnewline
247 & 0.408548 & 0.817095 & 0.591452 \tabularnewline
248 & 0.468192 & 0.936383 & 0.531808 \tabularnewline
249 & 0.408883 & 0.817766 & 0.591117 \tabularnewline
250 & 0.351446 & 0.702892 & 0.648554 \tabularnewline
251 & 0.379318 & 0.758636 & 0.620682 \tabularnewline
252 & 0.360834 & 0.721668 & 0.639166 \tabularnewline
253 & 0.349618 & 0.699236 & 0.650382 \tabularnewline
254 & 0.490578 & 0.981156 & 0.509422 \tabularnewline
255 & 0.544933 & 0.910135 & 0.455067 \tabularnewline
256 & 0.493005 & 0.986011 & 0.506995 \tabularnewline
257 & 0.518766 & 0.962469 & 0.481234 \tabularnewline
258 & 0.745342 & 0.509316 & 0.254658 \tabularnewline
259 & 0.720387 & 0.559226 & 0.279613 \tabularnewline
260 & 0.657205 & 0.685589 & 0.342795 \tabularnewline
261 & 0.580581 & 0.838838 & 0.419419 \tabularnewline
262 & 0.50176 & 0.99648 & 0.49824 \tabularnewline
263 & 0.650735 & 0.69853 & 0.349265 \tabularnewline
264 & 0.650624 & 0.698752 & 0.349376 \tabularnewline
265 & 0.613016 & 0.773969 & 0.386984 \tabularnewline
266 & 0.602508 & 0.794984 & 0.397492 \tabularnewline
267 & 0.494375 & 0.988749 & 0.505625 \tabularnewline
268 & 0.438242 & 0.876484 & 0.561758 \tabularnewline
269 & 0.336027 & 0.672055 & 0.663973 \tabularnewline
270 & 0.696574 & 0.606852 & 0.303426 \tabularnewline
271 & 0.918779 & 0.162441 & 0.0812206 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263726&T=5

[TABLE]
[ROW][C]Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]p-values[/C][C]Alternative Hypothesis[/C][/ROW]
[ROW][C]breakpoint index[/C][C]greater[/C][C]2-sided[/C][C]less[/C][/ROW]
[ROW][C]8[/C][C]0.539602[/C][C]0.920796[/C][C]0.460398[/C][/ROW]
[ROW][C]9[/C][C]0.802037[/C][C]0.395926[/C][C]0.197963[/C][/ROW]
[ROW][C]10[/C][C]0.699743[/C][C]0.600514[/C][C]0.300257[/C][/ROW]
[ROW][C]11[/C][C]0.611321[/C][C]0.777358[/C][C]0.388679[/C][/ROW]
[ROW][C]12[/C][C]0.635987[/C][C]0.728026[/C][C]0.364013[/C][/ROW]
[ROW][C]13[/C][C]0.533484[/C][C]0.933031[/C][C]0.466516[/C][/ROW]
[ROW][C]14[/C][C]0.537552[/C][C]0.924896[/C][C]0.462448[/C][/ROW]
[ROW][C]15[/C][C]0.840744[/C][C]0.318511[/C][C]0.159256[/C][/ROW]
[ROW][C]16[/C][C]0.843212[/C][C]0.313576[/C][C]0.156788[/C][/ROW]
[ROW][C]17[/C][C]0.858811[/C][C]0.282378[/C][C]0.141189[/C][/ROW]
[ROW][C]18[/C][C]0.809724[/C][C]0.380553[/C][C]0.190276[/C][/ROW]
[ROW][C]19[/C][C]0.819128[/C][C]0.361743[/C][C]0.180872[/C][/ROW]
[ROW][C]20[/C][C]0.772509[/C][C]0.454982[/C][C]0.227491[/C][/ROW]
[ROW][C]21[/C][C]0.855834[/C][C]0.288332[/C][C]0.144166[/C][/ROW]
[ROW][C]22[/C][C]0.838206[/C][C]0.323587[/C][C]0.161794[/C][/ROW]
[ROW][C]23[/C][C]0.795185[/C][C]0.409629[/C][C]0.204815[/C][/ROW]
[ROW][C]24[/C][C]0.746497[/C][C]0.507007[/C][C]0.253503[/C][/ROW]
[ROW][C]25[/C][C]0.799632[/C][C]0.400735[/C][C]0.200368[/C][/ROW]
[ROW][C]26[/C][C]0.755888[/C][C]0.488224[/C][C]0.244112[/C][/ROW]
[ROW][C]27[/C][C]0.833414[/C][C]0.333171[/C][C]0.166586[/C][/ROW]
[ROW][C]28[/C][C]0.833702[/C][C]0.332597[/C][C]0.166298[/C][/ROW]
[ROW][C]29[/C][C]0.795799[/C][C]0.408402[/C][C]0.204201[/C][/ROW]
[ROW][C]30[/C][C]0.769763[/C][C]0.460474[/C][C]0.230237[/C][/ROW]
[ROW][C]31[/C][C]0.736437[/C][C]0.527125[/C][C]0.263563[/C][/ROW]
[ROW][C]32[/C][C]0.714081[/C][C]0.571837[/C][C]0.285919[/C][/ROW]
[ROW][C]33[/C][C]0.678874[/C][C]0.642252[/C][C]0.321126[/C][/ROW]
[ROW][C]34[/C][C]0.766154[/C][C]0.467691[/C][C]0.233846[/C][/ROW]
[ROW][C]35[/C][C]0.736915[/C][C]0.526171[/C][C]0.263085[/C][/ROW]
[ROW][C]36[/C][C]0.871524[/C][C]0.256953[/C][C]0.128476[/C][/ROW]
[ROW][C]37[/C][C]0.96989[/C][C]0.0602195[/C][C]0.0301097[/C][/ROW]
[ROW][C]38[/C][C]0.970673[/C][C]0.0586533[/C][C]0.0293266[/C][/ROW]
[ROW][C]39[/C][C]0.961502[/C][C]0.0769964[/C][C]0.0384982[/C][/ROW]
[ROW][C]40[/C][C]0.982889[/C][C]0.0342219[/C][C]0.0171109[/C][/ROW]
[ROW][C]41[/C][C]0.978555[/C][C]0.0428893[/C][C]0.0214446[/C][/ROW]
[ROW][C]42[/C][C]0.972319[/C][C]0.0553621[/C][C]0.027681[/C][/ROW]
[ROW][C]43[/C][C]0.985868[/C][C]0.0282645[/C][C]0.0141323[/C][/ROW]
[ROW][C]44[/C][C]0.984028[/C][C]0.0319439[/C][C]0.0159719[/C][/ROW]
[ROW][C]45[/C][C]0.979751[/C][C]0.0404984[/C][C]0.0202492[/C][/ROW]
[ROW][C]46[/C][C]0.991596[/C][C]0.0168078[/C][C]0.00840388[/C][/ROW]
[ROW][C]47[/C][C]0.989865[/C][C]0.020271[/C][C]0.0101355[/C][/ROW]
[ROW][C]48[/C][C]0.986905[/C][C]0.0261897[/C][C]0.0130948[/C][/ROW]
[ROW][C]49[/C][C]0.987141[/C][C]0.0257178[/C][C]0.0128589[/C][/ROW]
[ROW][C]50[/C][C]0.983082[/C][C]0.033836[/C][C]0.016918[/C][/ROW]
[ROW][C]51[/C][C]0.978204[/C][C]0.0435926[/C][C]0.0217963[/C][/ROW]
[ROW][C]52[/C][C]0.987663[/C][C]0.0246732[/C][C]0.0123366[/C][/ROW]
[ROW][C]53[/C][C]0.985358[/C][C]0.0292846[/C][C]0.0146423[/C][/ROW]
[ROW][C]54[/C][C]0.985056[/C][C]0.0298871[/C][C]0.0149435[/C][/ROW]
[ROW][C]55[/C][C]0.988038[/C][C]0.0239243[/C][C]0.0119622[/C][/ROW]
[ROW][C]56[/C][C]0.985212[/C][C]0.0295767[/C][C]0.0147884[/C][/ROW]
[ROW][C]57[/C][C]0.991356[/C][C]0.0172886[/C][C]0.00864429[/C][/ROW]
[ROW][C]58[/C][C]0.993976[/C][C]0.0120472[/C][C]0.00602361[/C][/ROW]
[ROW][C]59[/C][C]0.992061[/C][C]0.0158789[/C][C]0.00793943[/C][/ROW]
[ROW][C]60[/C][C]0.990182[/C][C]0.0196361[/C][C]0.00981804[/C][/ROW]
[ROW][C]61[/C][C]0.987194[/C][C]0.0256123[/C][C]0.0128061[/C][/ROW]
[ROW][C]62[/C][C]0.983922[/C][C]0.0321557[/C][C]0.0160778[/C][/ROW]
[ROW][C]63[/C][C]0.983077[/C][C]0.0338465[/C][C]0.0169232[/C][/ROW]
[ROW][C]64[/C][C]0.979443[/C][C]0.0411134[/C][C]0.0205567[/C][/ROW]
[ROW][C]65[/C][C]0.983818[/C][C]0.032364[/C][C]0.016182[/C][/ROW]
[ROW][C]66[/C][C]0.982706[/C][C]0.0345881[/C][C]0.0172941[/C][/ROW]
[ROW][C]67[/C][C]0.979456[/C][C]0.041088[/C][C]0.020544[/C][/ROW]
[ROW][C]68[/C][C]0.975997[/C][C]0.0480066[/C][C]0.0240033[/C][/ROW]
[ROW][C]69[/C][C]0.970641[/C][C]0.0587178[/C][C]0.0293589[/C][/ROW]
[ROW][C]70[/C][C]0.966736[/C][C]0.0665281[/C][C]0.033264[/C][/ROW]
[ROW][C]71[/C][C]0.961652[/C][C]0.076696[/C][C]0.038348[/C][/ROW]
[ROW][C]72[/C][C]0.954791[/C][C]0.0904187[/C][C]0.0452094[/C][/ROW]
[ROW][C]73[/C][C]0.955617[/C][C]0.0887662[/C][C]0.0443831[/C][/ROW]
[ROW][C]74[/C][C]0.952255[/C][C]0.0954904[/C][C]0.0477452[/C][/ROW]
[ROW][C]75[/C][C]0.97842[/C][C]0.04316[/C][C]0.02158[/C][/ROW]
[ROW][C]76[/C][C]0.973014[/C][C]0.0539723[/C][C]0.0269862[/C][/ROW]
[ROW][C]77[/C][C]0.96936[/C][C]0.0612795[/C][C]0.0306398[/C][/ROW]
[ROW][C]78[/C][C]0.962512[/C][C]0.074975[/C][C]0.0374875[/C][/ROW]
[ROW][C]79[/C][C]0.955599[/C][C]0.0888021[/C][C]0.0444011[/C][/ROW]
[ROW][C]80[/C][C]0.950435[/C][C]0.09913[/C][C]0.049565[/C][/ROW]
[ROW][C]81[/C][C]0.940229[/C][C]0.119543[/C][C]0.0597713[/C][/ROW]
[ROW][C]82[/C][C]0.929707[/C][C]0.140587[/C][C]0.0702935[/C][/ROW]
[ROW][C]83[/C][C]0.922268[/C][C]0.155464[/C][C]0.0777321[/C][/ROW]
[ROW][C]84[/C][C]0.9092[/C][C]0.1816[/C][C]0.0908001[/C][/ROW]
[ROW][C]85[/C][C]0.896206[/C][C]0.207589[/C][C]0.103794[/C][/ROW]
[ROW][C]86[/C][C]0.87854[/C][C]0.24292[/C][C]0.12146[/C][/ROW]
[ROW][C]87[/C][C]0.861555[/C][C]0.276889[/C][C]0.138445[/C][/ROW]
[ROW][C]88[/C][C]0.895824[/C][C]0.208352[/C][C]0.104176[/C][/ROW]
[ROW][C]89[/C][C]0.879362[/C][C]0.241276[/C][C]0.120638[/C][/ROW]
[ROW][C]90[/C][C]0.866066[/C][C]0.267868[/C][C]0.133934[/C][/ROW]
[ROW][C]91[/C][C]0.918633[/C][C]0.162734[/C][C]0.0813672[/C][/ROW]
[ROW][C]92[/C][C]0.90465[/C][C]0.190701[/C][C]0.0953503[/C][/ROW]
[ROW][C]93[/C][C]0.928612[/C][C]0.142776[/C][C]0.0713879[/C][/ROW]
[ROW][C]94[/C][C]0.917987[/C][C]0.164025[/C][C]0.0820127[/C][/ROW]
[ROW][C]95[/C][C]0.903712[/C][C]0.192576[/C][C]0.0962879[/C][/ROW]
[ROW][C]96[/C][C]0.889521[/C][C]0.220958[/C][C]0.110479[/C][/ROW]
[ROW][C]97[/C][C]0.877834[/C][C]0.244332[/C][C]0.122166[/C][/ROW]
[ROW][C]98[/C][C]0.86657[/C][C]0.26686[/C][C]0.13343[/C][/ROW]
[ROW][C]99[/C][C]0.847046[/C][C]0.305907[/C][C]0.152954[/C][/ROW]
[ROW][C]100[/C][C]0.843154[/C][C]0.313692[/C][C]0.156846[/C][/ROW]
[ROW][C]101[/C][C]0.820873[/C][C]0.358254[/C][C]0.179127[/C][/ROW]
[ROW][C]102[/C][C]0.800961[/C][C]0.398078[/C][C]0.199039[/C][/ROW]
[ROW][C]103[/C][C]0.804619[/C][C]0.390761[/C][C]0.195381[/C][/ROW]
[ROW][C]104[/C][C]0.821727[/C][C]0.356546[/C][C]0.178273[/C][/ROW]
[ROW][C]105[/C][C]0.835079[/C][C]0.329842[/C][C]0.164921[/C][/ROW]
[ROW][C]106[/C][C]0.81408[/C][C]0.37184[/C][C]0.18592[/C][/ROW]
[ROW][C]107[/C][C]0.803175[/C][C]0.39365[/C][C]0.196825[/C][/ROW]
[ROW][C]108[/C][C]0.77951[/C][C]0.44098[/C][C]0.22049[/C][/ROW]
[ROW][C]109[/C][C]0.777069[/C][C]0.445861[/C][C]0.222931[/C][/ROW]
[ROW][C]110[/C][C]0.757952[/C][C]0.484095[/C][C]0.242048[/C][/ROW]
[ROW][C]111[/C][C]0.732978[/C][C]0.534043[/C][C]0.267022[/C][/ROW]
[ROW][C]112[/C][C]0.70415[/C][C]0.591699[/C][C]0.29585[/C][/ROW]
[ROW][C]113[/C][C]0.704986[/C][C]0.590027[/C][C]0.295014[/C][/ROW]
[ROW][C]114[/C][C]0.685117[/C][C]0.629767[/C][C]0.314883[/C][/ROW]
[ROW][C]115[/C][C]0.672067[/C][C]0.655867[/C][C]0.327933[/C][/ROW]
[ROW][C]116[/C][C]0.646568[/C][C]0.706863[/C][C]0.353432[/C][/ROW]
[ROW][C]117[/C][C]0.725063[/C][C]0.549875[/C][C]0.274937[/C][/ROW]
[ROW][C]118[/C][C]0.713718[/C][C]0.572565[/C][C]0.286282[/C][/ROW]
[ROW][C]119[/C][C]0.687595[/C][C]0.62481[/C][C]0.312405[/C][/ROW]
[ROW][C]120[/C][C]0.658954[/C][C]0.682093[/C][C]0.341046[/C][/ROW]
[ROW][C]121[/C][C]0.632028[/C][C]0.735944[/C][C]0.367972[/C][/ROW]
[ROW][C]122[/C][C]0.702013[/C][C]0.595973[/C][C]0.297987[/C][/ROW]
[ROW][C]123[/C][C]0.676723[/C][C]0.646554[/C][C]0.323277[/C][/ROW]
[ROW][C]124[/C][C]0.726413[/C][C]0.547175[/C][C]0.273587[/C][/ROW]
[ROW][C]125[/C][C]0.70316[/C][C]0.59368[/C][C]0.29684[/C][/ROW]
[ROW][C]126[/C][C]0.766262[/C][C]0.467477[/C][C]0.233738[/C][/ROW]
[ROW][C]127[/C][C]0.746398[/C][C]0.507205[/C][C]0.253602[/C][/ROW]
[ROW][C]128[/C][C]0.798813[/C][C]0.402374[/C][C]0.201187[/C][/ROW]
[ROW][C]129[/C][C]0.774004[/C][C]0.451993[/C][C]0.225996[/C][/ROW]
[ROW][C]130[/C][C]0.773731[/C][C]0.452538[/C][C]0.226269[/C][/ROW]
[ROW][C]131[/C][C]0.760999[/C][C]0.478003[/C][C]0.239001[/C][/ROW]
[ROW][C]132[/C][C]0.7383[/C][C]0.523399[/C][C]0.2617[/C][/ROW]
[ROW][C]133[/C][C]0.7514[/C][C]0.497201[/C][C]0.2486[/C][/ROW]
[ROW][C]134[/C][C]0.754292[/C][C]0.491415[/C][C]0.245708[/C][/ROW]
[ROW][C]135[/C][C]0.8416[/C][C]0.316801[/C][C]0.1584[/C][/ROW]
[ROW][C]136[/C][C]0.820302[/C][C]0.359395[/C][C]0.179698[/C][/ROW]
[ROW][C]137[/C][C]0.804622[/C][C]0.390756[/C][C]0.195378[/C][/ROW]
[ROW][C]138[/C][C]0.858494[/C][C]0.283012[/C][C]0.141506[/C][/ROW]
[ROW][C]139[/C][C]0.838554[/C][C]0.322891[/C][C]0.161446[/C][/ROW]
[ROW][C]140[/C][C]0.817361[/C][C]0.365279[/C][C]0.182639[/C][/ROW]
[ROW][C]141[/C][C]0.826429[/C][C]0.347142[/C][C]0.173571[/C][/ROW]
[ROW][C]142[/C][C]0.856424[/C][C]0.287151[/C][C]0.143576[/C][/ROW]
[ROW][C]143[/C][C]0.838263[/C][C]0.323474[/C][C]0.161737[/C][/ROW]
[ROW][C]144[/C][C]0.828529[/C][C]0.342941[/C][C]0.171471[/C][/ROW]
[ROW][C]145[/C][C]0.811012[/C][C]0.377977[/C][C]0.188988[/C][/ROW]
[ROW][C]146[/C][C]0.788106[/C][C]0.423788[/C][C]0.211894[/C][/ROW]
[ROW][C]147[/C][C]0.764319[/C][C]0.471362[/C][C]0.235681[/C][/ROW]
[ROW][C]148[/C][C]0.741549[/C][C]0.516902[/C][C]0.258451[/C][/ROW]
[ROW][C]149[/C][C]0.71886[/C][C]0.56228[/C][C]0.28114[/C][/ROW]
[ROW][C]150[/C][C]0.700288[/C][C]0.599424[/C][C]0.299712[/C][/ROW]
[ROW][C]151[/C][C]0.716725[/C][C]0.56655[/C][C]0.283275[/C][/ROW]
[ROW][C]152[/C][C]0.749378[/C][C]0.501244[/C][C]0.250622[/C][/ROW]
[ROW][C]153[/C][C]0.725615[/C][C]0.54877[/C][C]0.274385[/C][/ROW]
[ROW][C]154[/C][C]0.733137[/C][C]0.533725[/C][C]0.266863[/C][/ROW]
[ROW][C]155[/C][C]0.707928[/C][C]0.584143[/C][C]0.292072[/C][/ROW]
[ROW][C]156[/C][C]0.700106[/C][C]0.599788[/C][C]0.299894[/C][/ROW]
[ROW][C]157[/C][C]0.678387[/C][C]0.643225[/C][C]0.321613[/C][/ROW]
[ROW][C]158[/C][C]0.657081[/C][C]0.685839[/C][C]0.342919[/C][/ROW]
[ROW][C]159[/C][C]0.633605[/C][C]0.732789[/C][C]0.366395[/C][/ROW]
[ROW][C]160[/C][C]0.626391[/C][C]0.747219[/C][C]0.373609[/C][/ROW]
[ROW][C]161[/C][C]0.616194[/C][C]0.767611[/C][C]0.383806[/C][/ROW]
[ROW][C]162[/C][C]0.591481[/C][C]0.817039[/C][C]0.408519[/C][/ROW]
[ROW][C]163[/C][C]0.563364[/C][C]0.873272[/C][C]0.436636[/C][/ROW]
[ROW][C]164[/C][C]0.531287[/C][C]0.937425[/C][C]0.468713[/C][/ROW]
[ROW][C]165[/C][C]0.558173[/C][C]0.883655[/C][C]0.441827[/C][/ROW]
[ROW][C]166[/C][C]0.562218[/C][C]0.875563[/C][C]0.437782[/C][/ROW]
[ROW][C]167[/C][C]0.543085[/C][C]0.913831[/C][C]0.456915[/C][/ROW]
[ROW][C]168[/C][C]0.518321[/C][C]0.963357[/C][C]0.481679[/C][/ROW]
[ROW][C]169[/C][C]0.547477[/C][C]0.905047[/C][C]0.452523[/C][/ROW]
[ROW][C]170[/C][C]0.51358[/C][C]0.972839[/C][C]0.48642[/C][/ROW]
[ROW][C]171[/C][C]0.528205[/C][C]0.94359[/C][C]0.471795[/C][/ROW]
[ROW][C]172[/C][C]0.534514[/C][C]0.930972[/C][C]0.465486[/C][/ROW]
[ROW][C]173[/C][C]0.556142[/C][C]0.887715[/C][C]0.443858[/C][/ROW]
[ROW][C]174[/C][C]0.520839[/C][C]0.958322[/C][C]0.479161[/C][/ROW]
[ROW][C]175[/C][C]0.485117[/C][C]0.970233[/C][C]0.514883[/C][/ROW]
[ROW][C]176[/C][C]0.454625[/C][C]0.909249[/C][C]0.545375[/C][/ROW]
[ROW][C]177[/C][C]0.459194[/C][C]0.918388[/C][C]0.540806[/C][/ROW]
[ROW][C]178[/C][C]0.462415[/C][C]0.92483[/C][C]0.537585[/C][/ROW]
[ROW][C]179[/C][C]0.443525[/C][C]0.88705[/C][C]0.556475[/C][/ROW]
[ROW][C]180[/C][C]0.437418[/C][C]0.874835[/C][C]0.562582[/C][/ROW]
[ROW][C]181[/C][C]0.452035[/C][C]0.90407[/C][C]0.547965[/C][/ROW]
[ROW][C]182[/C][C]0.688249[/C][C]0.623502[/C][C]0.311751[/C][/ROW]
[ROW][C]183[/C][C]0.658512[/C][C]0.682976[/C][C]0.341488[/C][/ROW]
[ROW][C]184[/C][C]0.630317[/C][C]0.739367[/C][C]0.369683[/C][/ROW]
[ROW][C]185[/C][C]0.627035[/C][C]0.74593[/C][C]0.372965[/C][/ROW]
[ROW][C]186[/C][C]0.600534[/C][C]0.798933[/C][C]0.399466[/C][/ROW]
[ROW][C]187[/C][C]0.564326[/C][C]0.871349[/C][C]0.435674[/C][/ROW]
[ROW][C]188[/C][C]0.563485[/C][C]0.87303[/C][C]0.436515[/C][/ROW]
[ROW][C]189[/C][C]0.541348[/C][C]0.917305[/C][C]0.458652[/C][/ROW]
[ROW][C]190[/C][C]0.554409[/C][C]0.891183[/C][C]0.445591[/C][/ROW]
[ROW][C]191[/C][C]0.577901[/C][C]0.844199[/C][C]0.422099[/C][/ROW]
[ROW][C]192[/C][C]0.541017[/C][C]0.917967[/C][C]0.458983[/C][/ROW]
[ROW][C]193[/C][C]0.505892[/C][C]0.988216[/C][C]0.494108[/C][/ROW]
[ROW][C]194[/C][C]0.480054[/C][C]0.960107[/C][C]0.519946[/C][/ROW]
[ROW][C]195[/C][C]0.443928[/C][C]0.887857[/C][C]0.556072[/C][/ROW]
[ROW][C]196[/C][C]0.419273[/C][C]0.838546[/C][C]0.580727[/C][/ROW]
[ROW][C]197[/C][C]0.422196[/C][C]0.844392[/C][C]0.577804[/C][/ROW]
[ROW][C]198[/C][C]0.387081[/C][C]0.774161[/C][C]0.612919[/C][/ROW]
[ROW][C]199[/C][C]0.401205[/C][C]0.80241[/C][C]0.598795[/C][/ROW]
[ROW][C]200[/C][C]0.389805[/C][C]0.779611[/C][C]0.610195[/C][/ROW]
[ROW][C]201[/C][C]0.461334[/C][C]0.922668[/C][C]0.538666[/C][/ROW]
[ROW][C]202[/C][C]0.515007[/C][C]0.969986[/C][C]0.484993[/C][/ROW]
[ROW][C]203[/C][C]0.523593[/C][C]0.952815[/C][C]0.476407[/C][/ROW]
[ROW][C]204[/C][C]0.484682[/C][C]0.969363[/C][C]0.515318[/C][/ROW]
[ROW][C]205[/C][C]0.500868[/C][C]0.998264[/C][C]0.499132[/C][/ROW]
[ROW][C]206[/C][C]0.487212[/C][C]0.974424[/C][C]0.512788[/C][/ROW]
[ROW][C]207[/C][C]0.470791[/C][C]0.941582[/C][C]0.529209[/C][/ROW]
[ROW][C]208[/C][C]0.473283[/C][C]0.946567[/C][C]0.526717[/C][/ROW]
[ROW][C]209[/C][C]0.793873[/C][C]0.412254[/C][C]0.206127[/C][/ROW]
[ROW][C]210[/C][C]0.797457[/C][C]0.405087[/C][C]0.202543[/C][/ROW]
[ROW][C]211[/C][C]0.771383[/C][C]0.457234[/C][C]0.228617[/C][/ROW]
[ROW][C]212[/C][C]0.738768[/C][C]0.522464[/C][C]0.261232[/C][/ROW]
[ROW][C]213[/C][C]0.746975[/C][C]0.50605[/C][C]0.253025[/C][/ROW]
[ROW][C]214[/C][C]0.720912[/C][C]0.558177[/C][C]0.279088[/C][/ROW]
[ROW][C]215[/C][C]0.693084[/C][C]0.613832[/C][C]0.306916[/C][/ROW]
[ROW][C]216[/C][C]0.663127[/C][C]0.673747[/C][C]0.336873[/C][/ROW]
[ROW][C]217[/C][C]0.623356[/C][C]0.753289[/C][C]0.376644[/C][/ROW]
[ROW][C]218[/C][C]0.60878[/C][C]0.782441[/C][C]0.39122[/C][/ROW]
[ROW][C]219[/C][C]0.587362[/C][C]0.825275[/C][C]0.412638[/C][/ROW]
[ROW][C]220[/C][C]0.551258[/C][C]0.897483[/C][C]0.448742[/C][/ROW]
[ROW][C]221[/C][C]0.508068[/C][C]0.983863[/C][C]0.491932[/C][/ROW]
[ROW][C]222[/C][C]0.571664[/C][C]0.856671[/C][C]0.428336[/C][/ROW]
[ROW][C]223[/C][C]0.531639[/C][C]0.936722[/C][C]0.468361[/C][/ROW]
[ROW][C]224[/C][C]0.498304[/C][C]0.996609[/C][C]0.501696[/C][/ROW]
[ROW][C]225[/C][C]0.473291[/C][C]0.946583[/C][C]0.526709[/C][/ROW]
[ROW][C]226[/C][C]0.441353[/C][C]0.882707[/C][C]0.558647[/C][/ROW]
[ROW][C]227[/C][C]0.504149[/C][C]0.991703[/C][C]0.495851[/C][/ROW]
[ROW][C]228[/C][C]0.464444[/C][C]0.928888[/C][C]0.535556[/C][/ROW]
[ROW][C]229[/C][C]0.508138[/C][C]0.983723[/C][C]0.491862[/C][/ROW]
[ROW][C]230[/C][C]0.485913[/C][C]0.971826[/C][C]0.514087[/C][/ROW]
[ROW][C]231[/C][C]0.478834[/C][C]0.957667[/C][C]0.521166[/C][/ROW]
[ROW][C]232[/C][C]0.457133[/C][C]0.914266[/C][C]0.542867[/C][/ROW]
[ROW][C]233[/C][C]0.441733[/C][C]0.883466[/C][C]0.558267[/C][/ROW]
[ROW][C]234[/C][C]0.446319[/C][C]0.892639[/C][C]0.553681[/C][/ROW]
[ROW][C]235[/C][C]0.529294[/C][C]0.941412[/C][C]0.470706[/C][/ROW]
[ROW][C]236[/C][C]0.490568[/C][C]0.981135[/C][C]0.509432[/C][/ROW]
[ROW][C]237[/C][C]0.56144[/C][C]0.87712[/C][C]0.43856[/C][/ROW]
[ROW][C]238[/C][C]0.51359[/C][C]0.97282[/C][C]0.48641[/C][/ROW]
[ROW][C]239[/C][C]0.489509[/C][C]0.979018[/C][C]0.510491[/C][/ROW]
[ROW][C]240[/C][C]0.497082[/C][C]0.994164[/C][C]0.502918[/C][/ROW]
[ROW][C]241[/C][C]0.497938[/C][C]0.995876[/C][C]0.502062[/C][/ROW]
[ROW][C]242[/C][C]0.582573[/C][C]0.834853[/C][C]0.417427[/C][/ROW]
[ROW][C]243[/C][C]0.532612[/C][C]0.934775[/C][C]0.467388[/C][/ROW]
[ROW][C]244[/C][C]0.519042[/C][C]0.961917[/C][C]0.480958[/C][/ROW]
[ROW][C]245[/C][C]0.50349[/C][C]0.99302[/C][C]0.49651[/C][/ROW]
[ROW][C]246[/C][C]0.455244[/C][C]0.910488[/C][C]0.544756[/C][/ROW]
[ROW][C]247[/C][C]0.408548[/C][C]0.817095[/C][C]0.591452[/C][/ROW]
[ROW][C]248[/C][C]0.468192[/C][C]0.936383[/C][C]0.531808[/C][/ROW]
[ROW][C]249[/C][C]0.408883[/C][C]0.817766[/C][C]0.591117[/C][/ROW]
[ROW][C]250[/C][C]0.351446[/C][C]0.702892[/C][C]0.648554[/C][/ROW]
[ROW][C]251[/C][C]0.379318[/C][C]0.758636[/C][C]0.620682[/C][/ROW]
[ROW][C]252[/C][C]0.360834[/C][C]0.721668[/C][C]0.639166[/C][/ROW]
[ROW][C]253[/C][C]0.349618[/C][C]0.699236[/C][C]0.650382[/C][/ROW]
[ROW][C]254[/C][C]0.490578[/C][C]0.981156[/C][C]0.509422[/C][/ROW]
[ROW][C]255[/C][C]0.544933[/C][C]0.910135[/C][C]0.455067[/C][/ROW]
[ROW][C]256[/C][C]0.493005[/C][C]0.986011[/C][C]0.506995[/C][/ROW]
[ROW][C]257[/C][C]0.518766[/C][C]0.962469[/C][C]0.481234[/C][/ROW]
[ROW][C]258[/C][C]0.745342[/C][C]0.509316[/C][C]0.254658[/C][/ROW]
[ROW][C]259[/C][C]0.720387[/C][C]0.559226[/C][C]0.279613[/C][/ROW]
[ROW][C]260[/C][C]0.657205[/C][C]0.685589[/C][C]0.342795[/C][/ROW]
[ROW][C]261[/C][C]0.580581[/C][C]0.838838[/C][C]0.419419[/C][/ROW]
[ROW][C]262[/C][C]0.50176[/C][C]0.99648[/C][C]0.49824[/C][/ROW]
[ROW][C]263[/C][C]0.650735[/C][C]0.69853[/C][C]0.349265[/C][/ROW]
[ROW][C]264[/C][C]0.650624[/C][C]0.698752[/C][C]0.349376[/C][/ROW]
[ROW][C]265[/C][C]0.613016[/C][C]0.773969[/C][C]0.386984[/C][/ROW]
[ROW][C]266[/C][C]0.602508[/C][C]0.794984[/C][C]0.397492[/C][/ROW]
[ROW][C]267[/C][C]0.494375[/C][C]0.988749[/C][C]0.505625[/C][/ROW]
[ROW][C]268[/C][C]0.438242[/C][C]0.876484[/C][C]0.561758[/C][/ROW]
[ROW][C]269[/C][C]0.336027[/C][C]0.672055[/C][C]0.663973[/C][/ROW]
[ROW][C]270[/C][C]0.696574[/C][C]0.606852[/C][C]0.303426[/C][/ROW]
[ROW][C]271[/C][C]0.918779[/C][C]0.162441[/C][C]0.0812206[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263726&T=5

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263726&T=5

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Goldfeld-Quandt test for Heteroskedasticity
p-valuesAlternative Hypothesis
breakpoint indexgreater2-sidedless
80.5396020.9207960.460398
90.8020370.3959260.197963
100.6997430.6005140.300257
110.6113210.7773580.388679
120.6359870.7280260.364013
130.5334840.9330310.466516
140.5375520.9248960.462448
150.8407440.3185110.159256
160.8432120.3135760.156788
170.8588110.2823780.141189
180.8097240.3805530.190276
190.8191280.3617430.180872
200.7725090.4549820.227491
210.8558340.2883320.144166
220.8382060.3235870.161794
230.7951850.4096290.204815
240.7464970.5070070.253503
250.7996320.4007350.200368
260.7558880.4882240.244112
270.8334140.3331710.166586
280.8337020.3325970.166298
290.7957990.4084020.204201
300.7697630.4604740.230237
310.7364370.5271250.263563
320.7140810.5718370.285919
330.6788740.6422520.321126
340.7661540.4676910.233846
350.7369150.5261710.263085
360.8715240.2569530.128476
370.969890.06021950.0301097
380.9706730.05865330.0293266
390.9615020.07699640.0384982
400.9828890.03422190.0171109
410.9785550.04288930.0214446
420.9723190.05536210.027681
430.9858680.02826450.0141323
440.9840280.03194390.0159719
450.9797510.04049840.0202492
460.9915960.01680780.00840388
470.9898650.0202710.0101355
480.9869050.02618970.0130948
490.9871410.02571780.0128589
500.9830820.0338360.016918
510.9782040.04359260.0217963
520.9876630.02467320.0123366
530.9853580.02928460.0146423
540.9850560.02988710.0149435
550.9880380.02392430.0119622
560.9852120.02957670.0147884
570.9913560.01728860.00864429
580.9939760.01204720.00602361
590.9920610.01587890.00793943
600.9901820.01963610.00981804
610.9871940.02561230.0128061
620.9839220.03215570.0160778
630.9830770.03384650.0169232
640.9794430.04111340.0205567
650.9838180.0323640.016182
660.9827060.03458810.0172941
670.9794560.0410880.020544
680.9759970.04800660.0240033
690.9706410.05871780.0293589
700.9667360.06652810.033264
710.9616520.0766960.038348
720.9547910.09041870.0452094
730.9556170.08876620.0443831
740.9522550.09549040.0477452
750.978420.043160.02158
760.9730140.05397230.0269862
770.969360.06127950.0306398
780.9625120.0749750.0374875
790.9555990.08880210.0444011
800.9504350.099130.049565
810.9402290.1195430.0597713
820.9297070.1405870.0702935
830.9222680.1554640.0777321
840.90920.18160.0908001
850.8962060.2075890.103794
860.878540.242920.12146
870.8615550.2768890.138445
880.8958240.2083520.104176
890.8793620.2412760.120638
900.8660660.2678680.133934
910.9186330.1627340.0813672
920.904650.1907010.0953503
930.9286120.1427760.0713879
940.9179870.1640250.0820127
950.9037120.1925760.0962879
960.8895210.2209580.110479
970.8778340.2443320.122166
980.866570.266860.13343
990.8470460.3059070.152954
1000.8431540.3136920.156846
1010.8208730.3582540.179127
1020.8009610.3980780.199039
1030.8046190.3907610.195381
1040.8217270.3565460.178273
1050.8350790.3298420.164921
1060.814080.371840.18592
1070.8031750.393650.196825
1080.779510.440980.22049
1090.7770690.4458610.222931
1100.7579520.4840950.242048
1110.7329780.5340430.267022
1120.704150.5916990.29585
1130.7049860.5900270.295014
1140.6851170.6297670.314883
1150.6720670.6558670.327933
1160.6465680.7068630.353432
1170.7250630.5498750.274937
1180.7137180.5725650.286282
1190.6875950.624810.312405
1200.6589540.6820930.341046
1210.6320280.7359440.367972
1220.7020130.5959730.297987
1230.6767230.6465540.323277
1240.7264130.5471750.273587
1250.703160.593680.29684
1260.7662620.4674770.233738
1270.7463980.5072050.253602
1280.7988130.4023740.201187
1290.7740040.4519930.225996
1300.7737310.4525380.226269
1310.7609990.4780030.239001
1320.73830.5233990.2617
1330.75140.4972010.2486
1340.7542920.4914150.245708
1350.84160.3168010.1584
1360.8203020.3593950.179698
1370.8046220.3907560.195378
1380.8584940.2830120.141506
1390.8385540.3228910.161446
1400.8173610.3652790.182639
1410.8264290.3471420.173571
1420.8564240.2871510.143576
1430.8382630.3234740.161737
1440.8285290.3429410.171471
1450.8110120.3779770.188988
1460.7881060.4237880.211894
1470.7643190.4713620.235681
1480.7415490.5169020.258451
1490.718860.562280.28114
1500.7002880.5994240.299712
1510.7167250.566550.283275
1520.7493780.5012440.250622
1530.7256150.548770.274385
1540.7331370.5337250.266863
1550.7079280.5841430.292072
1560.7001060.5997880.299894
1570.6783870.6432250.321613
1580.6570810.6858390.342919
1590.6336050.7327890.366395
1600.6263910.7472190.373609
1610.6161940.7676110.383806
1620.5914810.8170390.408519
1630.5633640.8732720.436636
1640.5312870.9374250.468713
1650.5581730.8836550.441827
1660.5622180.8755630.437782
1670.5430850.9138310.456915
1680.5183210.9633570.481679
1690.5474770.9050470.452523
1700.513580.9728390.48642
1710.5282050.943590.471795
1720.5345140.9309720.465486
1730.5561420.8877150.443858
1740.5208390.9583220.479161
1750.4851170.9702330.514883
1760.4546250.9092490.545375
1770.4591940.9183880.540806
1780.4624150.924830.537585
1790.4435250.887050.556475
1800.4374180.8748350.562582
1810.4520350.904070.547965
1820.6882490.6235020.311751
1830.6585120.6829760.341488
1840.6303170.7393670.369683
1850.6270350.745930.372965
1860.6005340.7989330.399466
1870.5643260.8713490.435674
1880.5634850.873030.436515
1890.5413480.9173050.458652
1900.5544090.8911830.445591
1910.5779010.8441990.422099
1920.5410170.9179670.458983
1930.5058920.9882160.494108
1940.4800540.9601070.519946
1950.4439280.8878570.556072
1960.4192730.8385460.580727
1970.4221960.8443920.577804
1980.3870810.7741610.612919
1990.4012050.802410.598795
2000.3898050.7796110.610195
2010.4613340.9226680.538666
2020.5150070.9699860.484993
2030.5235930.9528150.476407
2040.4846820.9693630.515318
2050.5008680.9982640.499132
2060.4872120.9744240.512788
2070.4707910.9415820.529209
2080.4732830.9465670.526717
2090.7938730.4122540.206127
2100.7974570.4050870.202543
2110.7713830.4572340.228617
2120.7387680.5224640.261232
2130.7469750.506050.253025
2140.7209120.5581770.279088
2150.6930840.6138320.306916
2160.6631270.6737470.336873
2170.6233560.7532890.376644
2180.608780.7824410.39122
2190.5873620.8252750.412638
2200.5512580.8974830.448742
2210.5080680.9838630.491932
2220.5716640.8566710.428336
2230.5316390.9367220.468361
2240.4983040.9966090.501696
2250.4732910.9465830.526709
2260.4413530.8827070.558647
2270.5041490.9917030.495851
2280.4644440.9288880.535556
2290.5081380.9837230.491862
2300.4859130.9718260.514087
2310.4788340.9576670.521166
2320.4571330.9142660.542867
2330.4417330.8834660.558267
2340.4463190.8926390.553681
2350.5292940.9414120.470706
2360.4905680.9811350.509432
2370.561440.877120.43856
2380.513590.972820.48641
2390.4895090.9790180.510491
2400.4970820.9941640.502918
2410.4979380.9958760.502062
2420.5825730.8348530.417427
2430.5326120.9347750.467388
2440.5190420.9619170.480958
2450.503490.993020.49651
2460.4552440.9104880.544756
2470.4085480.8170950.591452
2480.4681920.9363830.531808
2490.4088830.8177660.591117
2500.3514460.7028920.648554
2510.3793180.7586360.620682
2520.3608340.7216680.639166
2530.3496180.6992360.650382
2540.4905780.9811560.509422
2550.5449330.9101350.455067
2560.4930050.9860110.506995
2570.5187660.9624690.481234
2580.7453420.5093160.254658
2590.7203870.5592260.279613
2600.6572050.6855890.342795
2610.5805810.8388380.419419
2620.501760.996480.49824
2630.6507350.698530.349265
2640.6506240.6987520.349376
2650.6130160.7739690.386984
2660.6025080.7949840.397492
2670.4943750.9887490.505625
2680.4382420.8764840.561758
2690.3360270.6720550.663973
2700.6965740.6068520.303426
2710.9187790.1624410.0812206






Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level290.109848NOK
10% type I error level440.166667NOK

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity \tabularnewline
Description & # significant tests & % significant tests & OK/NOK \tabularnewline
1% type I error level & 0 & 0 & OK \tabularnewline
5% type I error level & 29 & 0.109848 & NOK \tabularnewline
10% type I error level & 44 & 0.166667 & NOK \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=263726&T=6

[TABLE]
[ROW][C]Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity[/C][/ROW]
[ROW][C]Description[/C][C]# significant tests[/C][C]% significant tests[/C][C]OK/NOK[/C][/ROW]
[ROW][C]1% type I error level[/C][C]0[/C][C]0[/C][C]OK[/C][/ROW]
[ROW][C]5% type I error level[/C][C]29[/C][C]0.109848[/C][C]NOK[/C][/ROW]
[ROW][C]10% type I error level[/C][C]44[/C][C]0.166667[/C][C]NOK[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=263726&T=6

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=263726&T=6

As an alternative you can also use a QR Code:  
QR Code


The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity
Description# significant tests% significant testsOK/NOK
1% type I error level00OK
5% type I error level290.109848NOK
10% type I error level440.166667NOK


Figures (Output of Computation)

Figure 1
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Figure 2
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Figure 3
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Figure 4
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Figure 5
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Figure 6
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Figure 7
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Figure 8
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Figure 9
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Figure 10
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Input Parameters & R Code

Parameters (Session):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
Parameters (R input):
par1 = 1 ; par2 = Do not include Seasonal Dummies ; par3 = No Linear Trend ;
R code (references can be found in the software module):
library(lattice)
library(lmtest)
n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test
par1 <- as.numeric(par1)
x <- t(y)
k <- length(x[1,])
n <- length(x[,1])
x1 <- cbind(x[,par1], x[,1:k!=par1])
mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1])
colnames(x1) <- mycolnames #colnames(x)[par1]
x <- x1
if (par3 == 'First Differences'){
x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep='')))
for (i in 1:n-1) {
for (j in 1:k) {
x2[i,j] <- x[i+1,j] - x[i,j]
}
}
x <- x2
}
if (par2 == 'Include Monthly Dummies'){
x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep ='')))
for (i in 1:11){
x2[seq(i,n,12),i] <- 1
}
x <- cbind(x, x2)
}
if (par2 == 'Include Quarterly Dummies'){
x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep ='')))
for (i in 1:3){
x2[seq(i,n,4),i] <- 1
}
x <- cbind(x, x2)
}
k <- length(x[1,])
if (par3 == 'Linear Trend'){
x <- cbind(x, c(1:n))
colnames(x)[k+1] <- 't'
}
x
k <- length(x[1,])
df <- as.data.frame(x)
(mylm <- lm(df))
(mysum <- summary(mylm))
if (n > n25) {
kp3 <- k + 3
nmkm3 <- n - k - 3
gqarr <- array(NA, dim=c(nmkm3-kp3+1,3))
numgqtests <- 0
numsignificant1 <- 0
numsignificant5 <- 0
numsignificant10 <- 0
for (mypoint in kp3:nmkm3) {
j <- 0
numgqtests <- numgqtests + 1
for (myalt in c('greater', 'two.sided', 'less')) {
j <- j + 1
gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value
}
if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1
if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1
if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1
}
gqarr
}
bitmap(file='test0.png')
plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index')
points(x[,1]-mysum$resid)
grid()
dev.off()
bitmap(file='test1.png')
plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index')
grid()
dev.off()
bitmap(file='test2.png')
hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals')
grid()
dev.off()
bitmap(file='test3.png')
densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals')
dev.off()
bitmap(file='test4.png')
qqnorm(mysum$resid, main='Residual Normal Q-Q Plot')
qqline(mysum$resid)
grid()
dev.off()
(myerror <- as.ts(mysum$resid))
bitmap(file='test5.png')
dum <- cbind(lag(myerror,k=1),myerror)
dum
dum1 <- dum[2:length(myerror),]
dum1
z <- as.data.frame(dum1)
z
plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals')
lines(lowess(z))
abline(lm(z))
grid()
dev.off()
bitmap(file='test6.png')
acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function')
grid()
dev.off()
bitmap(file='test7.png')
pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function')
grid()
dev.off()
bitmap(file='test8.png')
opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0))
plot(mylm, las = 1, sub='Residual Diagnostics')
par(opar)
dev.off()
if (n > n25) {
bitmap(file='test9.png')
plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint')
grid()
dev.off()
}
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE)
a<-table.row.end(a)
myeq <- colnames(x)[1]
myeq <- paste(myeq, '[t] = ', sep='')
for (i in 1:k){
if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '')
myeq <- paste(myeq, signif(mysum$coefficients[i,1],6), sep=' ')
if (rownames(mysum$coefficients)[i] != '(Intercept)') {
myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='')
if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='')
}
}
myeq <- paste(myeq, ' + e[t]')
a<-table.row.start(a)
a<-table.element(a, myeq)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,hyperlink('ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Variable',header=TRUE)
a<-table.element(a,'Parameter',header=TRUE)
a<-table.element(a,'S.D.',header=TRUE)
a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE)
a<-table.element(a,'2-tail p-value',header=TRUE)
a<-table.element(a,'1-tail p-value',header=TRUE)
a<-table.row.end(a)
for (i in 1:k){
a<-table.row.start(a)
a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE)
a<-table.element(a,signif(mysum$coefficients[i,1],6))
a<-table.element(a, signif(mysum$coefficients[i,2],6))
a<-table.element(a, signif(mysum$coefficients[i,3],4))
a<-table.element(a, signif(mysum$coefficients[i,4],6))
a<-table.element(a, signif(mysum$coefficients[i,4]/2,6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple R',1,TRUE)
a<-table.element(a, signif(sqrt(mysum$r.squared),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'R-squared',1,TRUE)
a<-table.element(a, signif(mysum$r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Adjusted R-squared',1,TRUE)
a<-table.element(a, signif(mysum$adj.r.squared,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (value)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[1],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[2],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE)
a<-table.element(a, signif(mysum$fstatistic[3],6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'p-value',1,TRUE)
a<-table.element(a, signif(1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3]),6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residual Standard Deviation',1,TRUE)
a<-table.element(a, signif(mysum$sigma,6))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Sum Squared Residuals',1,TRUE)
a<-table.element(a, signif(sum(myerror*myerror),6))
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Time or Index', 1, TRUE)
a<-table.element(a, 'Actuals', 1, TRUE)
a<-table.element(a, 'Interpolation
Forecast', 1, TRUE)
a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE)
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,i, 1, TRUE)
a<-table.element(a,signif(x[i],6))
a<-table.element(a,signif(x[i]-mysum$resid[i],6))
a<-table.element(a,signif(mysum$resid[i],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable4.tab')
if (n > n25) {
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-values',header=TRUE)
a<-table.element(a,'Alternative Hypothesis',3,header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'breakpoint index',header=TRUE)
a<-table.element(a,'greater',header=TRUE)
a<-table.element(a,'2-sided',header=TRUE)
a<-table.element(a,'less',header=TRUE)
a<-table.row.end(a)
for (mypoint in kp3:nmkm3) {
a<-table.row.start(a)
a<-table.element(a,mypoint,header=TRUE)
a<-table.element(a,signif(gqarr[mypoint-kp3+1,1],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,2],6))
a<-table.element(a,signif(gqarr[mypoint-kp3+1,3],6))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable5.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Description',header=TRUE)
a<-table.element(a,'# significant tests',header=TRUE)
a<-table.element(a,'% significant tests',header=TRUE)
a<-table.element(a,'OK/NOK',header=TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'1% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant1,6))
a<-table.element(a,signif(numsignificant1/numgqtests,6))
if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'5% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant5,6))
a<-table.element(a,signif(numsignificant5/numgqtests,6))
if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'10% type I error level',header=TRUE)
a<-table.element(a,signif(numsignificant10,6))
a<-table.element(a,signif(numsignificant10/numgqtests,6))
if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK'
a<-table.element(a,dum)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable6.tab')
}